Frequently Asked Questions

We use our weekly group meetings to stay in touch with each other’s work. Every member of the lab summarises their week of work on Notion, a platform we use to organise our group. It also gives us an opportunity every week to ask questions, to get advice on an issue or just to flag up an interesting topic someone came across to every other member in the lab. Our hour-long weekly meeting then consists of going through these updates to ensure everyone is up to speed with everyone else’s work and to learn something new via a presentation or workshop put on by a member of the lab. We rotate around the group to give everyone a chance to present their work, invite a guest speaker, practice a talk for a conference, put on a coding workshop or just tell us about something they do in their spare time. Staying in touch with each other is also very important to us. We use Slack to communicate with other members of the team. This makes it easy to ask each other for help if we are stuck with our own research, to point out interesting papers and to share our achievements with each other. We also organise social events outside of the department. For example, we like to get together to enjoy a pint at a pub or share each other’s interests by finding like-minded people for running events.

We are a very diverse group of PhD students and Postdocs who come from all across the world. Many of us even come from a different background than statistics. Hence, we welcome everyone interested in advancing the development of methods, theory and/or applications in statistics and/or healthcare to apply to our group.

If you’re new to applying for PhD positions in the UK, then you might not be familiar with how to write a personal statement. A personal statement is your one chance to really tell your future supervisor or the programme you’re applying to why you’re motivated to do research and pursue a PhD. There is no wrong or right way to write a personal statement. However, here are some topics that you can choose to include in your statement. Firstly, what has inspired you to pursue research? Was it a mentor, a particular area of statistics or problem in healthcare or perhaps a book or an article? Secondly, what have you done to foster your interest in the field you’re applying for? Have you pursued any particular courses or maybe participated in a hackathon? Thirdly, what do you want to get out of a PhD? Think about what goals you want to achieve during your PhD or what experiences you would like to have within your programme and how we as a lab can help you to achieve those.

Enhancing your knowledge in any area of statistics you’re interested in is a great way of preparing for a PhD in Statistics. If you do come from a non-traditional background outside of the field of statistics or mathematics, focusing on a good foundation in linear algebra and analysis is always a good idea. Coursera or other open course software can provide great opportunities to gain new skills in one of the areas of research our lab focuses on, for example causal inference. The following books can also be a starting point to prepare for a PhD in our group: An Introduction to Statistical Learning by Gareth James et al. The Elements of Statistical Learning by Trevor Hastie et al. Pattern Recognition and Machine Learning by Christopher Bishop Bayesian Data Analysis by Andrew Gelman et al. In the end though, all of these materials are merely suggestions if you need a place to start enhancing your statistics skills.

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If you have any specific questions about anyone’s research or about life as a PhD student, then feel free to reach out to any member of our lab. We’re happy to help! Any questions with respect to the general administration of our group, can be answered by Chris Holmes’ personal assistant Anne Hardy (ahendy@turing.ac.uk). If you want to get in touch about working with Chris Holmes, then please message him directly (cholmes@turing.ac.uk). However, be aware that he receives a high volume of messages and it may take a while for him to reply to you.