All posts by duncanastle

Bringing home the bacon: how to budget a grant application

Economic_impactRather than attempt a single blog covering all aspects of grant-writing, the wonderfully talented Sue Fletcher-Watson and I are continuing our blog series of advice to newly-fledged researchers by focusing on the challenges of costing a new grant.  Costing a grant means working out exactly where money will be spent, and being realistic about what it is going to cost. While it might seem like a tiresome administrative job, setting the budget has a big influence on your chances of success – both in terms of winning the funding and administering the project successfully.  It’s also an area where junior PIs are offered little or no guidance.

Let’s start with a few definitions.

Grant budgets are often divided into direct and indirect costs.  In a nutshell, direct costs are for things that just wouldn’t happen without the grant – wages for dedicated staff in new posts, paying participants for their time, the cost of any questionnaires or other materials you’re using. Indirect costs are contributions to things which would be paid anyway – like a portion of the time of an existing member of staff. You might cost for 5% of the salary of a technician, or senior advisor, which should equate to them spending a couple of hours per week on your project.

Another key phrase is Full Economic Costing, or FEC (don’t smirk). This is when a funder pays for various indirect costs and estates costs linked to your grant.  For example, a University provides buildings with heating and electricity, furniture and IT support, kitchens and meeting rooms. Staff on your grant will have access to a library and various support services.  All of these cost money and FEC is a way to assign some of that cost to incoming grants.  Not all funders cover FEC (e.g. charities tend not to, but UK research councils do make a contribution). Warning: FEC is always way more than you think. It can as much as double the cost of a single member of staff. So if there is an upper limit on what you can apply for, and FEC is included in this, you need to rein in your plans for what you’ll spend on equipment or post-doc salaries. Seek advice early on from a grants officer (more on this below).


Budgeting basics

You’re going to want to start with a nice Excel spreadsheet or similar – ask a colleague if they have an old one you can use as a template. It might be that your department has a financial administrator that can send you an up-to-date one – Universities have a habit of changing the details of how costs are calculated. Once you have your template, it can be easiest at the start to break down costs by activity – so you list all the participant payment, questionnaires, and travel costs associated with Study 1, Study 2 etc. However, when you submit your budget to the funder, you will want to group them by category.  All the travel costs will get summed together, and all the ‘consumables’ (anything that gets used once and can’t be used again – like postage or IQ-test forms – as distinct from “equipment” which can be re-used, like a laptop) will be in a different total. So make sure you label each cost according to type and then you can easily re-order your file and get the totals you need.

Each funder asks for costs organised in subtly different ways too.  They might want them broken down by year of the project, or use particular headings. EU funding want salary costs organised into “person-hours” which are utterly fiendish. Some funders might define “equipment” as only things that cost £2000 or more.  Others might pay for salaries but only allow them to be a certain proportion of the total budget. Check these constraints at the start and make sure you label and organise your budget accordingly.


Getting support and approval

Another key thing to check up front is the relevant permissions you need to go through, in your host institution. At the University of Cambridge (and probably others), certain forms may need submitting weeks in advance (sometimes months), and in many cases these will need some details from your budget. Check this out well in advance to avoid stress. Salaries in particular will need to be aligned with your institution’s pay-scales.  You should have a conversation with someone – probably a grants officer in your department – about the right pay grade to cost for a research assistant with a Masters degree, versus a lab technician, versus a post-doc. Don’t cost at the bottom point of the grade for a new post that you are going to advertise – costing at the middle or top of a grade range will give you freedom to negotiate with the applicant and offer an attractive salary. Normally the amount you should put in your budget for, say, a two-year full time post-doc, will be provided by the grants officer. You don’t just google it like Sue did with her first ever grant! Get the ballpark figures early on so you know what you’ve got to play with in the total budget. And always remember that your grants officer is being constantly bombarded with requests for costs, often at very short notice.  Contact them early on, keep them in the loop, and agree a rough timeline for preparing the application as partners.

Some funders only cover partial costs for large items of equipment.  Others won’t pay salary contributions for existing staff but will pay for teaching “buy out”.  This is when a grant will pay the salary of someone (normally at a mid-level pay grade) to replace the time that a senior lecturer or professor might otherwise have spent teaching.  This frees-up the Prof to help with your grant, while costing the original funder a lot less. If you have these sorts of constraints on the funding, make sure you understand them and, crucially, try to get something in writing from your department to guarantee that they will comply with the grant terms and provide any top-up funding you will need.


Costing staff

Staff will normally be the biggest cost. If you’re applying for a Fellowship you’ll probably be requesting your full-time salary and maybe a %FTE (full-time equivalent: 20% FTE = one working day per week) for a senior colleague. A contribution to the time of a department administrator is also a great idea if there’s someone available, and you will have tasks for them – they could run expenses claims, book travel and monitor your budgets, saving you valuable time that you’d rather spend on science. Try not to ask for favours or trade authorship on articles for work – if you can, pay for things like specialist statistics and programming support, or for access to an assessment space. Otherwise, if the project gets funded, you are potentially beholden to others’ goodwill and availability to get things done.

You might also employ a research assistant or post-doc. Think carefully about the kind of skills you need, the level of independence you want from your staff, and the number of days per week you need them.  While it might seem like having someone more experienced is always a good thing, actually recruiting a research assistant with a good Masters degree is much better if you have a tightly-defined project and want someone to just get on with it. Post-docs, and PhD students, will have agendas that extend beyond the goals of your project.  While we don’t mean to suggest you shouldn’t also be offering an RA career-development opportunities and intellectual input to the work, their career stage means that just by recruiting participants, collecting and analysing data they are building and extending their skills. You need a good match between what you’re asking your employees to do, what they already know, and what they are ready to learn.


What else should I ask for?

Other big costs will be conferences, including travel, registration, accommodation – budget generously for these and try to specify the meetings so the reviewers can see you have considered carefully the appropriate place to share your findings.  Don’t just cost for you to attend – bring your team along too, or at least give each of them one chance to attend a scientific meeting. Another way to support your staff is to ensure you cost for some training expenses – obviously these need to be relevant to the project but it also means they will finish their time working with you with more skills than when they started.

You might want to cost for a study advisory board including community representatives – their travel to meetings, some good quality catering, maybe a stipend. If you think this is overkill or too expensive for your project, you can at least cost an “honorarium” (one-off payment) for one or two consultants to advise on your work. Sue pays autistic consultants on all new autism projects now, normally aiming for £500 per year for about ten “contact points”.  A contact point might be commenting on documents by email, attending a meeting to design the methods, or advising on recruitment pathways. Be generous in your funds for participant reimbursement too, normally estimated as an hourly rate with extra for their travel costs. For children, budget for a box of gifts that they can choose from at the end of an assessment session. If working with charities or schools you might want to include a one-off gift to the organisation. If doing an online survey you can offer a prize draw, which increases response rates without pushing your budget through the roof.

Don’t neglect the impact costs either.  Open access fees for journal articles are important – though some funders like the Wellcome Trust cover these for you under a separate budget. If you want to reach out to stakeholders with your results think about costing for a graphic designer, professional printing, or an animator to help you share your findings creatively. Budget generously for dissemination events – you don’t want your exciting ideas buried because of a lack of resources. Funders are becoming increasingly suspicious of researchers promising the world in terms of impact, but with no budget attached.


What about cost effectiveness?

A grant should be cost-effective.  Reviewers will be specifically asked whether they think your work represents good value for money. This doesn’t mean though that you should just cut cut cut. An under-funded project is a big risk and reviewers and funding committees will be reluctant to support something that doesn’t seem appropriately resourced. On the other hand, if you want multiple staff, or large items of new equipment you will need to properly justify these.  In the case of staff, you should be able to describe their responsibilities and these should clearly match to their proposed pay-grade and full or part-time hours. An easy way to save costs if you need to is to ask whether you need staff for the entire duration of the project – can you set it up yourself and just employ an RA when data collection begins?

In the case of equipment, if you are buying large and expensive items, reviewers might well ask themselves why your department doesn’t have these already, and whether you know how to use them properly. Tackle these concerns head on – maybe you have tons of EEG experience, but you need brand new kit because you’re going to be working with infants for the first time.

A successful grant application requires so much more than a good research idea. Your costs are a key way to show that you have thought about the practical aspects of your research.  You have a clear plan, appropriately resourced. By costing for community consultants, open access fees, or staff conference attendance, you show the reviewers your commitment to ethical science and good lab management. Budgeting your research should be an integral part of a funding application process so don’t leave it as a final afterthought.


Be thorough. Be practical. Be a good scientist.



It’s a jungle out there: bagging a post-doc job


The incomparable Sue Fletcher-Watson and I continue our intermittent blog series on academic life today, this time focusing on the stressful post-PhD employment scene.  There are a number of options for those who want to stay in academia post-PhD, all highly competitive and with unique stressors. Today, we’re talking about one of the most common scenarios: applying for an advertised pot-doc research role in someone else’s lab. In this case, a PI has secured a grant already and is now advertising a clearly defined job, for someone to carry out the project. So how do you get your application to stand out?  How can you impress at interview?  Here’s a few tips, based on our recent experiences of being on the other side of the interview table.

Address ALL the job criteria, thoroughly but succinctly

Job adverts normally list essential and desirable criteria. In your application, compose a cover letter which specifically demonstrates your ability to meet these criteria. You’d be surprised how many people don’t do this, instead providing what amounts to an abstract for their PhD.  This is all well and good, but remember that the selection panel will use the job criteria to rate applicants.  They won’t give you the benefit of the doubt – you must demonstrate what you can do.

It is tricky to do this succinctly of course, and criteria like “must have excellent communication skills” can be hard to prove.  “I have excellent communication skills” isn’t exactly convincing. Focus on experiences you’ve had and what they taught you.  e.g. “My PhD was supervised by academics from two very different disciplines (informatics, psychology), enabling me to develop my excellent communication skills.  I ran three novel eye-tracking experiments, recruiting more than 80 autistic adults in 12 months, showing my innovative approach to science and time management abilities”. This tells the panel something about your specific skills in a range of areas: research methods, project management, interpersonal skills.

Don’t give the panel extra work

Very occasionally there is a really good reason to contact the panel before the interview. You might have a pressing question about the planned start date for example, or want to ask about potential to do the role part time. However, even in these cases you’d probably do better to apply and then negotiate on the details afterwards, if you’re offered the job.  If they’ve decided you are the right candidate, they will be much more willing to adapt to your situation.

More commonly, people get in touch before the interviews to ask questions like “Am I eligible for the job?” This infuriating query amounts to a request to vet your application prior to seeing other candidates, which is entirely unreasonable. The answer to this is always the same: please read the job description and if you think you are eligible then apply. The second type of advance question is along the lines of a proposal to adapt the study: e.g. have you thought about adding in an fMRI element to this? This also gets Sue’s back up. By this stage, the proposal for funding will have been tweaked and adapted in response to comments from multiple co-applicants, internal and external reviewers. It may have been turned down by one or two funders previously. This is not a good time to start to question fundamental components of the design!

That said, we should note that asking at the interview about where in the protocol there is room to innovate and make your mark on the project is to be encouraged. No-one wants to work with a cipher, just make sure you ask this with a recognition that there is a fixed topic, budget and timeline which you must operate within.

For goodness’ sake, proof-read

Another way to demonstrate your excellent abilities is to show them off in the quality of your application documents. Most scientists will value thoroughness, clarity and precision. Illustrate these qualities by submitting a clearly laid-out CV and cover letter, without typos or grammatical errors. Save it as a pdf so the formatting won’t be messed up by the recipient’s Word template. Don’t submit additional attachments such as reference letters or transcripts of your grades (unless the job advert specifies these). These are superfluous to requirements and just add to the difficulty of screening large numbers of applicants.  It will not work in your favour.

Aim to submit 24 hours before the deadline so you can check the upload works OK.  Sue once applied for a job very close to the deadline, and found at the last minute that her application file size was larger than that allowed on the system.  Cue frantic panic, adapting the document to get under the limit.

Preparation, preparation, preparation

So, you’ve been invited to interview?  Well done! Probably only 4 or 5 people have got this far. Most panels will ask you to prepare something – often a short presentation.  Whatever you do, practice it a lot and keep it to time. Remember that you might be a bit slower on the day if you are nervous (though Sue and Duncan always speed up when anxious…).  Pay close attention to what you’ve been asked to do and stick to the remit. Duncan’s experience is that candidates often overrun… and he has now taken to cutting people off mid-sentence. Everyone should have the same time, and managing the time limit is one of the points of asking interviewees to give a talk.

Prepare for some standard questions: why do you want this job?  What skills and experiences will you bring to the team?  What do you think are the major challenges for this project? How does it fit in with your personal career goals? Make sure you are familiar with the definitions (or debates over definitions) of key terms linked to the project so you can use these confidently and fluently.

It might be that the project has some aspects which are outside your expertise. Sue recently advertised a job on an autism & bilingualism study. This topic is so under-studied that none of the candidates had detailed expertise in both areas. If this happens to you, make sure you read up on a few of the latest findings in the literature – familiarise yourself with the current big debates so you can mention them if asked. Don’t worry about becoming an expert overnight though – it’s OK to say “I haven’t done work in this area myself…” so long as you follow up with “…but I’ve read a handful of papers to prepare and I was struck by…”.  Your panel will like to see that you care enough about the job to do some reading and won’t expect you to know every detail.

Focus on your transferable skills

In your statement and CV, and when preparing for the interview (well done if you get that far!) pull out what type of things you have learned which will be relevant to the project. Your panel are looking for aptitude and abilities that transcend the specific topic.  Maybe you’ve never worked with brain scans, but you have processed and managed large, complex data sets. Maybe you haven’t done research with children, but you did volunteer on a play scheme in the past. Maybe you haven’t done working memory research but you have designed novel tasks to measure attention. Show how what you have done relates to the project by pulling out the common threads – ability to innovate, attention to detail, sensitivity to participant needs.

If you’ve had challenges in the past it is fine to mention these – for example if you’re asked about the experiences you bring to the project. The panel will sympathise with issues recruiting hard to reach populations or making sense of complex patterns in your data.  Make sure though that you present these as problem-solving experiences: this was difficult and this is how we solved the issue. Whatever you think of your former supervisor or boss, don’t complain about them at the interview (yes, this has happened!).

Where the role requires some technical skills, you may find that these are put to the test. Duncan uses a simple ‘data handling’ exercise in his interview process for postdocs. This is undertaken on the day of the interview. Candidates can use any package of their choosing (R, Matlab, Python, Excel), and are typically given 30 minutes to complete the exercise. Be aware that if you have said that you have programming skills then you may have to prove it.

Show 360º thinking

A good researcher will always have multiple levels of a project in mind.  These include the theoretical level – what motivates this research?  What can it tell us theoretically or mechanistically about the way the world works? This should, in turn, relate to the methodological level: how are we going to address this question? Will we develop new methods or work with existing tools? Then there’s the practical level: what resources are needed to carry out this project?  How will they be managed? And finally you will want to consider the human level: who will I be working with – in the research team and as participants? What do they need from me and how can I deliver it?

Thinking about the job you’re applying for at all of these levels encourages you to consider deeply the pertinent issues that will make the study a success. If you take this approach, you won’t go far wrong.

Of course, it is possible that after all this you won’t be offered the job.  If that happens, don’t be down-hearted.  In academia, putting yourself out there by applying for jobs, writing papers, giving talks, submitting grants and speaking up in your workplace is essential.  Knock-backs are a core part of the process and one which we must all learn to embrace and grow from. By all means, email the panel and ask for their feedback. But remember, in 90% of cases the difference between you and the successful candidate will be about fit for the role (e.g. specific experience in a specific skill) rather than anything you could have done differently.

So, go for it. Be brave. Be thorough. Be a good scientist.

Don’t rule the lab with an iron fist: tips for effective lab management


This is the latest in our semi-regular (trying to be regular) blog series, with the indomitable Sue Fletcher-Watson. The practical skills of being a good scientist are rarely taught but are vital. This is the subject for our series of blogs, and this time we are turning our attention to managing the lab.

You have your University position, you have research funding of some kind (whoop!), and the lab – you, your students, researchers and technicians – is starting to take shape. Managing the team effectively will make for happy and productive group members. This can turn into a virtuous cycle – lab members who enjoy what they are doing are a joy to manage, and make your life so much easier.

What follows is stuff we have learnt over the past few years. The points are broadly organised into two sections – firstly we discuss issues of organisation and management style, then we move onto the non-science elements of a successful lab.

  • Balance lab identity with flexibility

It might seem obvious, but a group needs a shared identity that their projects can hang off. This could be a series of over-arching questions, a particular sample of interest, a set of new methods you are advancing, or a core set of principles. A clear group identity helps lab members understand the overall picture, how their science is contributing, and how/where expertise can be shared. When Sue joined the Patrick Wild Centre and was given a branded PhD mug it made her feel one of the team. This kind of thing makes a real difference for new staff and students.

But be careful that your lab identity doesn’t kill off flexibility. It’s important that individual lab members are able to take intellectual ownership of their work, even if they are junior. In Duncan’s lab he focuses cognitive and brain development in childhood. When a potential student approached him with an interest in socio-economic status he was initially very reluctant. He could see it could easily turn into an intractable mush – that literature can be a real mess. But he went with it, and together they put together a project they were both happy with. Turns out, the student was amazing, the project highly successful, and this line of research now forms a main arm of his current research programme. Giving lab members intellectual ownership and being flexible about projects means that you give your students and staff permission to innovate. In science this is the most valuable thing of all, and an essential component of how we make progress.

So have a clear identity and make sure this is explicit, and understood by all members – but don’t sacrifice flexibility.

  • Balance easy wins and long-term goals

When starting your lab you will have various potential projects. In the early days when the lab is small you need to be strategic. Investing all of your energies (and those of your lab) in a single demanding, high-risk project, which may take several years to come to fruition, is unwise. When Duncan started his lab in Cambridge a very wise mentor told him to balance easy wins and long-term goals – alongside a large project he needed simpler experiments. This advice was invaluable. That big project took Duncan’s embryonic team 18 months to collect the data alone, and another 18 months or so to analyse fully. All the lab members were trying to build their CVs and could not afford an empty patch for 3 years. So along the way they published several standalone experimental papers, which made everyone feel more relaxed and meant they could establish ourselves as a lab.

(In the end that big project came to fruition and generated multiple big papers, so our patience was rewarded!).

Meanwhile, during Sue’s postdoc she designed a novel intervention and then evaluated it in a small randomised controlled trial.  That’s a long time to wait for your big paper. To make matters worse, she took maternity leave twice during the project! It was a tough time, waiting for that research to get out into the world, though writing a few review papers and getting the remainder of her PhD studies into journals helped pass the time!

  • Don’t rule your lab with an iron fist

We have all heard about those labs where the staff are not so much managed as subjugated (maybe there will be a blog on that, if we are feeling brave enough). Lab members are micromanaged, their outgoing emails vetted and they are subjected to surprise inspections. If you are tempted to run your lab in this way, or if this is your natural management style, our advice: just don’t.  It results in very unhappy lab members, creates needless extra work for you, and is ultimately pointless. If your lab members are not enjoying working within your group then they will not be productive. Running them like a sweatshop will do nothing to improve that.

A better approach is to have a clear role-setting process when each member joins the lab. Explain your role as the PI and their role as the post-doc (or whatever). This role-setting includes outlining expectations – mandatory meetings, duties within the group, initial goals, the schedule for your individual meetings etc. If you feel this has not been respected, then of course, pull them up and gently tell them that you want to change things. But don’t micro-manage your group.

  • Have regular meetings with minutes

Regular group meetings (we both have them fortnightly) provide a space for sharing experience, best practice, technical expertise, troubleshooting and peer support. They’re also a quick and easy way to get a snapshot of where everyone is up to on their projects. Good lab meetings will save you time, and build a happy team. Make sure you reserve a timeslot and don’t let them run over. If you fall into the habit of having needlessly long lab meetings they can easily become onerous. Keep them to time. When you meet, get members of the lab to take turns writing minutes. Sue’s lab stores these in a shared folder which is also crammed with resources to help lab members work independently – model ethics documents and cover letters, useful logos and campus maps.

Sometimes subgroups within your lab may need to meet without you – let them. This could be a really valuable way of them tackling various problems without you needing to expend any time. Don’t insist on being there for every discussion or meeting.


So far we have focussed on elements of lab organisation, strategy and management style. For the next set of points we turn our attention to the more interpersonal elements of running a successful lab.

  • Encourage your lab to have a social life

Within Duncan’s lab there is a designated Social Secretary, with the job of orchestrating lab social events (checking availability, garnering opinion of what people would like to do, making bookings etc). Make sure that any social events are not enforced, and remember that alcohol is not an essential component of social occasions! It is important not to make anyone feel excluded. N.B. some social activities like life drawing classes might be an unwise choice (sorry Joe), so try to stick to simple events that allow everyone an opportunity to chat without feeling uncomfortable.

Things to keep in mind: what is your role within these social situations? Remember that you still have to be these people’s boss come Monday morning. Have fun but don’t be unprofessional. No-nos include gossiping about your colleagues or asking intrusive questions about people’s personal lives. While taking to the dancefloor to bust a groove is a big YES.

  • Be a good mentor and keep an eye on wellbeing

Running a successful lab is also about keeping an eye on the wellbeing of those you manage. It’s important to let them know that you care. Both Sue and Duncan make a point of asking, even though everyone seems pretty happy most of the time. This makes lab members mindful of their own wellbeing and flags the fact that you are a person they can speak to if / when they struggle. If you’re doing an annual review, ask them if they’re happy with their work-life balance. Remind your lab group to take time off – especially PhD students who can fall for the myth that they ought to be working 7-day weeks. It can also be a good idea for lab members to have mentors outside the group. With their mentor they can discuss matters like job opportunities, or difficulties they are having with their PI (i.e. you!). It can also provide a valuable alternate perspective on their work.

There is always a slight tension about how much of your own personal life you expose lab members to. Both Sue and Duncan think it is important to show your lab members that you too are a human being, with your own stresses, frustrations and problems. In our experience, when you choose to be yourself with your lab members, and be honest about how you are doing, you give lab members permission to do likewise. It creates a safe space in which everyone feels that they can be themselves, and this is important in creating a supportive work environment. Don’t overshare, but do be yourself.

So there we have it, our tips on running an effective lab. Be flexible, be a human being, be a good scientist.

The Dos and Don’ts of PhD supervision

Myself and Sue Fletcher-Watson (you know, the fabulously clever one…) have been putting our minds to a series of blog posts, attempting to help the fledgling academic get to grips with some of their new professional duties.  This week it is a real classic – how to supervise a PhD student.


Being a good supervisor is not easy, and tricky relationships between students and supervisors are all too common (you may have direct experience yourself). Understanding and mutually agreeing upon the role of the student and the supervisor is a crucial starting point. Establishing these expectations is an important early step and will make navigating the PhD easier for all concerned. With a shared idea of where you are both starting from, and where you want to get to, together you can chart the path forward.  Hopefully these DOs and DON’Ts will help you get off on the right foot as a PhD supervisor.

  1. Managing your intellectual contribution

DO challenge their thinking…

A good PhD supervisor should question their student’s decision making – some part of your supervision meetings should be viva-like. Why are you doing this? How does this method answer this question? What do these data mean? Make sure your student understands what you’re doing and why – be explicit that you expect them to defend their interpretation of the literature / research plans NOT adhere to yours. It is important that they don’t feel that this is a test, with just one right answer.

When questioning your student, strike a balance between exploring alternatives, and making forward progress. Probing assumptions is important but don’t become a pedant; you need to recognise when is the time to question the fundamentals, and when is the time to move the debate on to the next decision.

DON’T make decisions for them…

Help students determine the next decision to be made (“now that we have selected our measures we need to consider what analysis framework we will use”) and also the parameters that constrain this decision… but remember that it is not your place to make the decisions for them. Flagging the consequences of the various choices is an excellent way to bring your experience to bear, without eclipsing the student. You may wish to highlight budget constraints, discuss the likely recruitment rate, or consider the consequences of a chosen data type in terms of analysis time and required skills. Help them see how each decision feeds back. Sue recently worked with a student to move from research question, to methods, to power calculation, to ideal sample size, and then – finding that the project budget was inadequate to support the sample target – back to RQ again. It’s tough for a student to have to re-visit earlier decisions but important to consider all the relevant factors before committing to data collection.

  1. Who’s in charge?

DO give them project management responsibility

Both Sue and Duncan run fortnightly lab group meetings with all their students and this is highly recommended as a way to check in and ensure no student gets left hanging. But don’t make the mistake of becoming your student’s project manager. Whether you prefer frequent informal check-ins or more formal supervisions that are spaced apart, your student should be in charge of monitoring actual progress against plans, and recording decisions. For formal meetings, they can provide an agenda, attachments and minutes, assigning action points to you and other supervisors, and chasing these if needed. They should monitor the budget, and develop excellent version control and data management skills.

This achieves a number of different goals simultaneously. First, it gives your student a chance to learn the generic project management skills which will be essential if they continue in an academic career, and useful if they leave academia too. Second, it helps to reinforce the sense that this is their project, since power and responsibility go hand in hand. Finally, it means that your role in the project is as an intellectual contributor, shaping and challenging the research, rather than wasting your skills and time on bureaucratic tasks.

DON’T make them a lackey to serve your professional goals

Graduate students are not cheap research assistants. They are highly talented early career researchers with independent funding (in the majority of cases) that has been awarded to them on merit. They have chosen to place their graduate research project in your lab. They are not there to conduct your research or write your papers. In any case, attempting this approach is self-defeating. Students soon realise that they are being taken advantage of, especially when they chat with friends in other labs. When students become unhappy and the trust in their supervisor breaks down, the whole process can become ineffective for everyone concerned. As the supervisor you are there to help and guide their project… not the other way around.

This can be really challenging when graduate projects are embedded within a larger funded project. How do you balance the commitment you’ve made to the funder alongside the need for students to have sufficient ownership? Firstly, think carefully about whether your project really lends itself to a graduate student. Highly specified and rigid projects need great research assistants rather than graduate students. Secondly, build in sufficient scope for individual projects and analyses, for example by collecting flexible data types (e.g. parent-child play samples) which invite novel analyses, and make sure that students are aware of any constraints before they start.


  1. What are they here to learn?


DO provide opportunities to learn skills which extend beyond the project goals

A successful graduate project is not just measured in terms of thesis or papers, but in the professional skills acquired and whether these help them launch a career in whichever direction they choose. This will mean allowing your students to learn skills necessary for their research, but also giving them broader opportunities: formal training courses, giving and hearing talks, visiting other labs or attending conferences. This is all to be encouraged, though be careful that it happens alongside research progress, rather than as a displacement activity. Towards the end of the PhD, as the student prepares to fly the nest, these activities can be an important way of building the connections that are necessary to be part of a scientific community and make the next step in their career.


DON’T expect them to achieve technical marvels without support

All too often supervisors see exciting new analyses in papers or in talks and want to bring those skills to their lab. But remember, if you cannot teach the students to do something, then who will? Duncan still tries to get his hands dirty with the code (and is humoured in this effort by his lab members), but often manages to underestimate how difficult some technical steps can be. Meanwhile, Sue is coming to terms with the fact that she will never fully understand R.

If you recommend new technical analyses, or development of innovative stimuli, then make sure you fully understand what you are asking of your student – allow sufficient time for this and provide appropriate support. When thinking of co-supervisors, don’t always go for the bigwig you are trying to cosy up to… often a more junior member of staff whose technical skills are up-to-date would be far more useful to your student. Also try and create a lab culture with good peer support. Just as ‘it takes a village to raise a child’, so “it takes a lab to supervise a PhD student”. Proper peer support mechanisms, shared problem solving and an open lab culture are important ingredients for giving students the proper support they need.

  1. Being reasonable

DO set clear expectations            

Step one of any PhD should be to create a project timeline.  Sue normally recommends a detailed 6-month plan alongside a sketched 3-year plan, both of which should be updated about quarterly. For a study which is broken down into a series of short experiments, a different model might be better. Whatever planning system you adopt, you should work with your student to set realistic deadlines for specific tasks, assuming a full time 9-5 working day and no more, and adhere to these. Model best practice by providing timely feedback at an appropriate level of detail – remember, you can give too much as well as too little feedback.

Think carefully about what sort of outputs to ask for – make them reasonable and appropriate to the task. You might want propose a lengthy piece of writing in the first six months, to demonstrate that your student has grasped the literature and can pull it together coherently to make a case for their chosen research.  But, depending on the project, it might also be a good idea to get them to contrast some differing theoretical models in a mini-presentation to your lab, create a table summarising key methodological details and findings from previous work, or publish a web page to prioritise community engagement with the project topic.

DON’T forget their mental health and work-life balance

PhD students might have recently moved from another country or city – they may be tackling cultural differences at work and socially. Simultaneous life changes often happen at the same time as a PhD – meeting a life partner, marriage, children. Your students might be living in rented and shared accommodation, with all the stresses that can bring.

Make sure your students go home at a reasonable hour.  If you must work outside office hours be clear you don’t expect the same from them. Remind them to take a holiday – especially if they have had a period of working hard (e.g. meeting a deadline, collecting data at weekends). Ensure that information about the University support services are available prominently in the lab.

Remember to take into account their personal lives when you are discussing project progress. Being honest about your own personal situation (without over-sharing) creates an environment where it is OK to talk about stuff happening outside the office. Looking after your students’ mental health doesn’t mean being soft, or turning a blind eye to missed deadlines or poor quality work – it means being proactive and taking action when you can see things aren’t going well.

What about the research??

We are planning another blog in the future about MSc and undergrad supervision which might address some other questions more closely tied to the research itself – how to design an encapsulated, realistic but also worthwhile piece of research, and how to structure this over time. But the success (or otherwise) of a PhD hangs on a lot more than just having a great idea and delivering it on time. We hope this post will help readers to reflect on their personal management style and think about how that impacts their students.

So, be humble. Be supportive. Be a good supervisor.

Reviewer 2 is not your nemesis – how to revise and resubmit

This is a blog piece is written with Sue Fletcher-Watson, a colleague of supreme wisdom and tact, ideally qualified for this particular post. It is a follow-up to our previous joint post about peer-review. We now turn our attention to the response to reviewers.


As with the role of reviewer, junior scientists submitting their work as authors are given little (if any) guidance on how to interact with their reviewers. Interactions with reviewers are an incredibly valuable opportunity to improve your manuscript and find the best way of presenting your science. However, all too often responding to reviewers is seen as an onerous chore, which partly reflects the attitude we take into the process. These exchanges largely happen in private and even though they play a critical role in academia, we rarely talk about them in public. We think this needs to change – here are some pointers for how to interact with your reviewers.

  • Engage with the spirit of the review

Your reviewers will be representative of a portion of your intended readership. Sometimes when reading reviewers’ comments we can find ourselves asking “have they even read the paper?!”. But if the reviewer has misunderstood some critical aspect of the paper then it is entirely possible that a proportion of the broader readership will also. An apparently misguided review, whilst admittedly frustrating, should be taken as a warning sign. Give yourself a day or two to settle your temper, and then recognise that this is your opportunity to make your argument clearer and more convincing.

Similarly, resist the temptation to undertake the minimal possible revisions in order to get your paper past the reviewers. If a reviewer makes a good point and you can think of ways of using your data to address it, then go for it, even if this goes beyond what they specified. Remember – this is your last chance to make this manuscript as good as it can be.

  • Be grateful and respectful. But don’t be afraid to disagree with your reviewers.

Writing a good review takes time. Thank the reviewers for their efforts. Be polite and respectful, even if you think a review is not particularly constructive. But don’t be afraid to disagree with reviewers. Sometimes reviewers ask you to do things that you don’t think are valid or wise, and it’s important to defend your work. No one wants a dog’s dinner of a paper… a sort of patchwork of awkwardly combined paragraphs designed to appease various reviewer comments. As the author you need to retain ownership of the work. This will mean that sometimes you need to explain why a recommendation has not been actioned. You can acknowledge the importance of a reviewer’s point, without including it in your manuscript.

We have both experienced reviewers who have requested changes we don’t feel are legitimate. Examples include the reviewer who requested a correlational analysis on a sub-group with a sample size of n=17. Or the reviewer who asked Sue to describe how her results, from a study with participants aged 18 and over, might relate to early signs of autism in infancy (answer: they have no bearing whatsoever and I’m not prepared to speculate in print). Or the reviewer who asked for inclusion of variables in a regression analysis which did not correlate with the outcome, (despite that being a clearly-stated criterion for inclusion in the analysis), on the basis of their personal hunch. In these cases, politely but firmly refusing to make a change may be the right thing to do, though you can nearly always provide some form of concession. For example, in the last case, you might include an extra justification, with a supporting citation, for your chosen regression method.

  • Give your response a clear and transparent structure

With any luck, your revised manuscript will go out to the same people who reviewed it the first time.  If you do a particularly good job of addressing their comments – and if the original comments themselves were largely minor – your editor may even decide your manuscript doesn’t need peer review a second time. In any case, to maximise the chances of a good result it is essential that you present your response clearly, concisely and fluently.

Start by copying and pasting the reviewer comments into a document.  Organise them into numbered lists, one for each reviewer.  This might mean breaking down multi-part comments into separate items, and you may also wish to paraphrase to make your response a bit more succinct.  However, beware of changing the reviewer’s intended meaning!

Then provide your responses under each numbered point, addressed to the editor (“The reviewer makes an excellent point and…”). In each case, try to: acknowledge the validity of what the reviewer is saying; briefly mention how you have addressed the point; give a page reference.  This ‘response to reviewers’ document should be accompanied by an updated manuscript in which any significant areas of new text , or heavily edited text, are highlighted something like this. Don’t submit a revised manuscript with tracked changes – these are too detailed and messy for a reviewer to have to navigate – and don’t feel the need to highlight every changed word.

If it’s an especially complicated or lengthy response, then it is sometimes a good idea to include a (very) pithy summary up top for the Editor, before you get to the reviewer-specific response. A handful of bullet points can help orient the Editor to the major changes that they can expect to find in the new version of your manuscript.

  • The response letter can be a great place to include additional analyses that didn’t make it into the paper

Often when exploring the impact of various design choices or testing the impact of assumptions on your analysis, additional comparisons can be very useful. We both often include additional analyses in our ‘response to reviewer’ letters. This aids transparency and can also be a useful way of showing reviewers that your findings are solid. Sometimes these will be analyses that have been explicitly asked for, but on other occasions you may well want to do this from your initiative. As reviewers we are both greatly impressed when authors use their own data to address a point, even if we didn’t explicitly ask them to do this.

One word of warning here, however. Remember that you don’t want to put an important piece of information or line of reasoning only in your response letter, if it ought also to be in the final manuscript. If you’ve completed an extra analysis as part of your consideration of a reviewer point, consider whether this might also have relevance to your readership when the paper is published.  It might be important to leave it out – you don’t want to include ‘red herring’ analyses or look like you are scraping the statistical barrel by testing ‘til the cows come home. But on the other hand, if the analysis directly answers a question which is likely to be in your reader’s mind, consider including it.  This could be as a supplement, linked online data set, or a simple statement: e.g. “we repeated all analyses excluding n=2 participants with epilepsy and results were the same”.

  • Sometimes you may need the nuclear option

We have both had experiences where we have been forced to make direct contact with the Action Editor. A caveat to all the points above is that there are occasions where reviewers attempt to block the publication of a manuscript unreasonably. Duncan had an experience of a reviewer who simply cut and paste their original review, and reused it across multiple subsequent rounds of revision. Duncan thought that his team had done a good job of addressing the reviewer’s concerns, where possible, but without any specific guidance from the reviewer they were at a loss to identify what they should do next. Having already satisfied two other reviewers, he decided to contact the Action Editor and explain the situation. They accepted the paper. Sue has blogged before about a paper reporting on a small RCT which was rejected for the simple reason that it reported a null result. She approached the Editor with her concern and it was agreed that the paper should be re-submitted as a new manuscript and sent out again for a fresh set of reviews. This shouldn’t be necessary, but sadly sometimes it is.

Editors will not be happy with authors trying to circumvent the proper review process, but in our experience they are sympathetic to authors when papers are blocked by unreasonable reviewers. After all, we have all been there. If this is the situation you find yourself in, be as diplomatic as possible and outline your concerns to the Editor.

In conclusion, much of what we want to say can probably be summed up with the following: This is not a tick-box exercise, but the last opportunity to improve your paper before it reaches your audience. Engage with your reviewers, be open-minded, and don’t be afraid to rethink.

Really, when it comes to responding to reviewers, the clue is in the name.  It’s a response, not a reaction – so be thoughtful, be engaged and be a good scientist.

Think you’re your own harshest critic? Try peer review…

Our latest blog post is written by me with the wonderful Sue Fletcher-Watson, a colleague whose intellectual excellence is only exceeded by her whit and charm.PeerReview.jpeg

Peer review is a lynch-pin of the scientific process and bookends every scientific project. But despite the crucial importance of the peer review process in determining what research gets funded and published, in our experience PhD students and early career researchers are rarely if ever offered training on how to conduct a good review. Academics frequently find themselves complaining about the unreasonable content and tone of the anonymous reviews they receive, which we attribute partly to a lack of explicit guidance on the review process. In this post we offer some pointers on writing a good review of a journal article.  We hope to help fledgling academics hone their craft, and also provide some insight into the mechanics of peer review for non-academic readers.

What’s my review for?

Before we launch into our list of things to avoid in the review process, let’s just agree what a review of an academic journal article is meant to do. You have one simple decision to make: does this paper add something to the sum of scientific knowledge? Remember of course that reporting a significant effect ≠ adding new knowledge, and similarly, a non-significant result can be highly informative. Don’t get sucked into too much detail – you are not a copy editor, proof-reader, or English-language critic. Beyond that, you will also want to consider whether the manuscript, in its current form, does the best job of presenting that new piece of knowledge. There’s a few specific ways (not) to go about this, so it looks like it might be time for a list…

  1. Remember, this is not YOUR paper

Reviewer 2 walks into a bar and declares that this isn’t the joke they would have written.

First rule of writing a good peer review: remember that this is not your paper. Neither is this a hypothetical study that you wished the authors had conducted. Realising this will have a massive impact on your view of another’s manuscript. The job is not to sculpt it into a paper you could have written. Your job as a reviewer is two-fold: i) make a decision as to the value of this piece of work for your field; and ii) help the authors to present the clearest possible account of their science.

Misunderstanding the role of the reviewer is perhaps at the heart of many peer review horror stories. Duncan does a lot of studies on cognitive training. Primarily he’s interested in the neural mechanisms of change, and tries to be very clear about that. But reviewers almost always ask “where are your far transfer measures?” because they want to assess the potential therapeutic benefit of the training. This is incredibly infuriating. The studies are not designed or powered for looking at this, but instead at something else of equal but different value.

Remember – you can’t ask them to report an imaginary study you wished they had conducted.

  1. Changing the framing, but not the predictions

In this current climate of concern over p-hacking and other nefarious, non-scientific procedures, a question we have to ask ourselves as reviewers is: are there some things I can’t ask them to change? We think the answer is yes – but it may be less than you think. For starters, you can ask authors to re-consider the framing of the study to make it more accurate. Let’s imagine they set out to investigate classroom practice, but used interviews not observations, and so ended up recording teacher attitudes instead. Their framing can end up a bit out of kilter with the methods and findings. As a reviewer, with a bit of distance from the work, you can be very helpful in highlighting this.

If you think there are findings which could be elucidated – for example by including a new covariate, or by running a test again with a specific sub-group excluded – you should feel free to ask.  At the same time, you need to respect that the authors might respond by saying that they think these analyses are not justified.  We all should avoid data-mining for significant results and reviewers should be aware of this risk.

What almost certainly shouldn’t be changed are any predictions being made at the outset. If these represent the authors’ honest, well-founded expectations then they need to be left alone.

However, there may be an exception to this rule… Imagine a paper (and we have both seen these) where the literature reviewed is relatively balanced, or sparse, such that it is impossible to make a concrete prediction about the expected pattern in the new data. And yet these authors have magically extracted hypotheses about the size and direction of effects which match up with their results. In this case, it may be legitimate to ask authors to re-inspect their lit review so that it provides a robust case to support their predictions. Another option is to say that, given the equivocal nature of the field, the study would be better set-up with exploratory research questions. This is a delicate business, and if in doubt, it might be a good place to write something specific to the editor explaining your quandary (more on this in number 5).

  1. Ensuring all the information is there for future readers

In the end the quality of a paper is not determined by the editor or the reviewers… but by those who read and cite it. As a reviewer imagine that you are a naïve reader and ask whether you have all the information you need to make an informed judgement. If you don’t, then request changes. This information could take many forms. In the Method Section, ask yourself whether someone could reasonably replicate the study on the basis of the information provided. In the Results ask whether there are potential confounds or complicating factors that readers are not told about. These kinds of changes are vital.

We also think it is totally legitimate to request that authors include possible alternative interpretations. The whole framing of a paper can sometimes reflect just one of multiple possible interpretations, which could somewhat mislead readers. As a reviewer be wise to this and cut through the spin. The bottom-line: readers should be presented with all information necessary for making up their own minds.

  1. Digging and showing off

There is nothing wrong with a short review. Sometimes papers are good. As an editor, Duncan sometimes feels like reviewers are really clutching at straws, desperate to identify things to comment on. Remember that as a reviewer you are not trying to impress either the authors or the editor. Don’t dig for dirt in order to pad the review or show how brainy you are.

Another pet hate is when reviewers introduce new criticisms in subsequent rounds of review. Certainly if the authors have introduced new analyses or data since the original submission, then yes, this deserves a fresh critique. But please please please don’t wait until they have addressed your initial concerns… and then introduce a fresh set on the same material. When reviewers start doing this it smacks of a desperate attempt to block a paper, thinly veiled by apparently legitimate concerns. Editors shouldn’t stand for that kind of nonsense, so don’t make them pull you up on it.

  1. Honesty about your expertise

You don’t know it all, and there is no point pretending that you do. You have been asked to review a paper because you have relevant expertise, but it isn’t necessarily the case that you are an expert in all aspects of the paper. Make that clear to the authors or the editor (the confidential editor comments box is quite useful for this).

It is increasingly the case that our science is interdisciplinary – we have found this is especially the case where we are developing new neuroimaging methods and applying them to novel populations (e.g. typically and atypically developing children). The papers are usually reviewed by either methods specialists or developmental psychologists, and the reviews can be radically different. This likely reflects the different expertise of the reviewers, and it helps both authors and editor where this is made explicit.

Is it ok to ask authors to cite your work? Controversial. Duncan never has, but Sue (shameless self-publicist) has done. We both agree that it is important to point out areas of the literature that are relevant but have not been covered by the paper – and this might include your own work. After all, there’s a reason why you’ve been selected as a relevant reviewer for this paper.

Now we know what not to do, what should you put in a review?

Start your review with one or two sentences summarising the main purpose of the paper: “This manuscript reports on a study with [population X] using [method Y] to address whether [this thing] affects [this other thing].”  It is also good to highlight one or two key strengths of the paper – interesting topic, clear writing style, novel method, robust analysis etc. The text of your review will be sent, in full and unedited, to the authors. Always remember that someone has slaved over the work being reported, and the article writing itself, and recognise these efforts.

Then follow with your verdict, in a nutshell.  You don’t need to say anything specific about whether the paper should / should not be published (and some journals actively don’t want you to be explicit about this) but you should try to draw out the main themes of your comments to help orient the authors to the specific items which follow.

The next section of your review should be split into two lists – major and minor comments. Major comments are often cross-cutting,   e.g. if you don’t think the conclusions are legitimate based on the results presented. Also in the major comments include anything requiring substantial work on the part of the authors,  like a return to the original data. You might also want to highlight pervasive issues with the writing here – such as poor grammar – but don’t get sucked into noting each individual example.

Minor comments should require less effort on the part of the authors, such as some re-phrasing of key sentences, or addition of extra detail (e.g. “please report confidence intervals as well as p-values”). In each case it is helpful to attach your comments to a specific page and paragraph, and sometimes a numbered line reference too.

At the bottom of the review, you might like to add your signature. Increasing numbers of reviewers are doing this as part of a movement towards more open science practices. But don’t feel obliged – especially if you are relatively junior in your field, it may be difficult to write an honest review without the safety of anonymity.

Ready to review?

So, hopefully any early career researchers reading this might feel a bit more confident about reviewing now. Our key advice is to ensure that your comments are constructive, and framed sensitively. Remember that you and the original authors are both on the same side – trying to get important science out into a public domain where it can have a positive influence on research and practice. Think about what the field needs, and what readers can learn from this paper.

Be kind. Be reasonable. Be a good scientist.