Access to Data Science: start your PhD journey with Compass

Want to find out what a modern PhD in Statistics and Data Science is like?

Access to Data Science provides an immersive experience for prospective PhD students. This fully-funded, two-day event will be hosted by Compass academics and PhD students in the Fry Building, home to the School of Mathematics at the University of Bristol.

Application deadline: Monday 18 October 2021

Event dates: Monday 8 November – Tuesday 9 November

Find out more about the event here

The purpose of this event is to increase all aspects of diversity amongst data science researchers. We particularly encourage applications from women and members of the LGBTQ+ and BAME communities to join us. 


What to expect from the Access to Data Science event:

  • attend seminars and guest lectures
  • take part in a hands-on workshop
  • have exclusive access to an application writing workshop
  • work with the current Compass PhD students
  • option to attend the Women and non-binary people in mathematics event.

Who can attend

We welcome participants from a range of numerate academic backgrounds, with undergraduate degrees in subjects such as computer science, economics, epidemiology, mathematics, statistics and physics.

We welcome applications from across the UK. Access to Data Science participants will be offered hotel accommodation, reimbursement of travel costs and meals for each day of the event.

Apply to Access to Data Science here 

First PAI-Link Seminar: Maciek Glowacki, Mauro Camara Escudero (University of Bristol) and Ben Winter (Bangor University)

New opportunity: AstraZeneca to fund Compass PhD project

Novel semi-supervised Bayesian learning to rapidly screen new oligonucleotide drugs for impurities.


Video: The Data Science behind COVID Modelling

We are excited to share Dr Daniel Lawson’s (Compass CDT Co-Director) latest video where he will tell you about the Data Science behind Bristol’s COVID Modelling.

Mathematics has had a hidden role in predicting how we can best fight COVID-19. How is mathematics used with data science and machine learning? Why is modelling epidemics such a hard problem? How can we do it better next time? What will data science be able to do in the future, and how do you become a part of it?

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