Back in 2014 I wrote this blog post about managing your supervisor. The post was a way to consolidate some thoughts about my preferred supervision style. Since then I have shared the link with every new student who comes to work with me and it has been hugely useful. Now, three years on, and with a lot more supervision experience under my belt, it feels like time for an update.
I realise this post might be of little interest to a lot of my subscribers – those outside academia, for example. However, as I have said before, I think a key goal of science communication should be not just to share findings but also to expose some of the process of research. If you do choose to read on, I hope that this post will give you some insight into (my thoughts about) the workings of academia and especially the nature of that most daunting of qualifications – the PhD.
One aspect worth emphasising is the sheer quantity of supervision, even for someone fairly lowly, as I am (I completed my own PhD less than ten years ago). In the 2016/2017 academic year I am supervising five PhD students, one Masters student, three undergraduate project students and two visiting students on placement in my group. At the same time, I have supported four students to seek PhD funding to start in September 2017, and have been in negotiations with two further new students who already have funded PhDs and might come to work on projects with me. For about half of these I am the first supervisor leading the supervision and about half I am a co-supervisor, which means slightly less responsibility but normally about the same intellectual input. Finally, I’ve also been involved in three post-doc funding bids*. I’ve probably turned down another dozen approaches from potential students. This scale was something that really struck my Autistic mentor when she and I first started working together, and it is an important detail to grasp for anyone who hopes to understand academic research.
One more preamble before I get stuck in: If you are one of my current or recent students reading this, please don’t over-think which of my points below might pertain to you. All of these are generalisations derived from working with a series of students at all levels, over the last few years. And while I focus on the PhD, the lessons described here apply pretty much to all student levels and probably post-docs too.
So, looking back, would you retract anything that you previously wrote on this topic?
Not really, no. I stand by my priorities from the original post. Essentially, my argument then was – get the administrative side of your project right, so that together we can spend our time on the intellectual issues. I identified five keys ways to get this right:
- Be passionate about what you want to do (and translate that passion into action)
- Be in control of your project – e.g. organise meetings, send an agenda and minutes, think carefully about recording your methods protocol and labelling your data. Version control is also essential so I always know which document is the most recent, or the ‘master file’ for your study ^.
- Be in charge of your supervisor – give them (me!) clear action points and deadlines for these. Keep them informed about progress, but think about funneling this into one weekly email with an overview, rather than sending a message for every new update / question.
- Manage your time – set deadlines, and be realistic about these. Fit them into whatever else is going on in your life.
- Be honest – when you make a mistake, say so and we’ll fix it together
And has anything new come up?
Some new things, some expansions of the above..
One thing I’ve started to talk about more and more is that a PhD is a piece of training which requires confrontation of your personal limits. With the best will in the world, your project is probably not going to change lives. You don’t have enough time, enough money or the skills to make that sort of difference. It is true that some PhDs do make a big splash – but whether this happens or not is almost certainly going to be a fluke. For every influential Does the autistic child have a theory of mind? there are dozens of non-significant results from similarly modest experimental designs which never see the light of day, let alone inspire an entirely new theoretical model. While publication bias is a major concern, which I won’t tackle here, it is also worth pointing out that scientific progress should ideally be based on a accumulation of data from a range of studies which all converge on the same finding. This is something you definitely won’t do within a PhD, but you might do across your career. So instead of worrying about whether your PhD will produce the result you want, think instead about this time as a chance for you to develop the skills and knowledge you need to go on to make that positive difference in the long term..
On the topic of training, one key skill you need to hone is insight into your own strengths and challenges as a researcher. Most Universities offer plenty of training courses on things like writing skills, how to get a grant or how to present at a conference. These are fab, but there are other things you need to develop yourself. First and foremost, I would argue, is an understanding of, and connection to, your “constituents”. The people whom you hope, as a researcher, to represent and benefit. Take the time to get to know some representatives of the community you are working to support – even if your PhD is entirely lab based and you never see any humans (especially then!). Understand their issues. At the very least, when it comes to sharing your findings you will want to know how to connect what you’ve found with community priorities and what language to use when doing so. Other skills can’t really be taught no matter how many courses you attend. If you don’t feel like a fluent writer or a confident speaker, recognise this and ask your supervisor to help you find opportunities to practice. The more you can do these things, the less challenging it will be when you reach the end of your studies and they become compulsory rather than (more or less) optional.
My personal style as a supervisor is quite… bureaucratic? As the previous post illustrates, I like my students to approach their PhD as project managers, doing things like developing good Gantt charts and effective time management. However this can easier said than done, especially as measuring progress in a PhD is such a challenge – when you start, you basically have one deadline which is three years away. So here are a few top tips for managing your time as a student:
Use a calendar – I think digital works best but paper is fine – to schedule not just meetings but also activities. My calendar uses colour codes to mark out meetings which are fixed, regular weekly activities, family responsibilities and flxible work which I have planned – but also might move if needed.- Mark out the time you need every week / month for regular professional activities (e.g. updating online profiles) and also for things like volunteering in your community, public engagement, or participation in student societies. This serves two purposes. First, you will make sure that these activities are maintained, rather than allowed to pile up until they become urgent. Second, you will gain clarity on how much time you are giving to these activities, helping you understand if and when they start to encroach on ‘core’ PhD jobs.
- Identify your own working style and circumstances. If you work at home some days, reflect on what activities are best completed at home (this can be good for quite writing time, or reading in an arm chair instead of at your desk) and which ones are best done in the office. Think about how much intellectual energy you have at the start of the day or the end and plan to do your hardest tasks when you are best able to achieve them. Don’t get side-tracked by emails as they come in – save them up and then work through your inbox at regular intervals (e.g. every other day).
Having said all that, don’t let good time management get in the way of research quality. Yes, set deadlines and make a plan for the sub-components of each study you carry out, as well as an overview of how they fit together But ultimately, if you need more time to prep a study in order to get it right, take that time. There is a real art to this, and while your supervisor can advise you, one day you will have to defend the decisions you make at a viva. So think of your Gantt chart, and any other documents around which you structure your PhD, as a living document, adaptable to your circumstances. It should be used as a tool to help you move forward with your research goals, rather than a rigid framework to make you feel smug / disappointed. In the PhD race, you want to be the Tortoise, not the Hare.
Finally, I think I ought to add something about supervisor workload here. As my career has progressed, I have got busier, not just in the number of projects on my plate but the range of topics they cover. I was talking to a colleague about this recently and we agreed that this is the switch from early-career to mid-career status in a nutshell. Like everyone else in academia – and almost any industry I guess – I feel very busy most of the time. But this doesn’t mean that you, as a student, don’t have a right to demand your fair share of my attention. Of course, this should be within reasonable limits – for example, try to anticipate when you will need to meet as I will struggle to make time for you at short notice (be mindful that if I do, that probably means I will be working on something else in the evening). Practice good email hygiene – save up your queries and send them to me in a group making it clear whether you are a) just keeping me informed, b) need action from me. In return, I will try to offer the same respect to you. BUT whatever you do, don’t avoid contacting me at all. If you put off getting in touch, or asking for the support that you need, the chances are that the result will be more work for both of us.
During your PhD, in many ways, you are your supervisor’s boss. You know where you want to get to, and when you need to arrive. Your supervisor can help you pack for the journey. They can tell you whether they think you should drive, or take the train. They can advise on nice places to stop en route. But they have never been to that destination – no-one has. Take control of your journey, and make sure you bring your supervisor along with you.
* A post-doc is someone who has a PhD and is working in research. It is short for “post-doctoral researcher”, i.e. after a doctorate, just as post-grad = after graduating. In my field and many others it is usual for people to have a period of 2-6 years after their PhD and before securing their first post as a lecturer in a University, when they will work on a series of normally short-term contracts in research as a post-doc. This is pretty stressful. In this time, post-docs have two main options: 1. apply for a research job on a project which is already funded or 2. seek their own funding, normally with the support of a more established co-applicant.
^ I am a bit nuts on version control at the moment. This term is borrowed from software development but I use it more prosaically to refer to document labels. Here’s my preferred method:
- use version numbers (e.g. v1, v2) to indicate successive versions so the highest number should always be the most recent version
- where minor changes are made, or for changes in-between group consultation, use v1a, v1b etc.
- the primary author of each document should be the only one who progresses a document from one version to the next
- other authors can add initials to the end of the filename when they have made edits or comments, but otherwise don’t change the name
- save all documents in a shared drive and share via that route only, as far as possible, so that more recent versions don’t get lost in email chain
- move old versions to an ‘archive’ sub-folder when they are no longer in use
- When creating a new document, think about assigning a name which will make sense to all readers. e.g. “SFW ESRC proposal ASD+bilingualism v1” rather than “grant proposal v1”.
NB: This system works for word documents (e.g. successive iterations of a journal article or PhD proposal) but for data it isn’t quite the same. In this case, the ideal scenario is that a database has new content added, but old data are never removed. This is achievable with careful planning of the basic database template. It should therefore be possible to maintain a single “master file” for your data with no version updates.
