Structure of UNRISK
A Centre for Doctoral Training (CDT) is a program that provides students with training and skills in high-priority science areas within the remit of the Natural Environment Research Council (NERC). CDTs have a well-defined scientific focus, strong collaboration with non-academic partners, and offer a more-substantial and focused training experience than a conventional PhD.
There is a lot of variation across CDTs. In UNRISK:
- You will be registered as a PhD student in one of the three universities. All students are supervised by at least two members of academic staff who can be in the same or different departments or universities. Co-supervisors can also join from industry partners.
- All of our PhD topics span two or more of the science themes: climate science, data science, and decisions.
- You will undertake a cohort-level training programme that includes a residential component. Our training programme covers all three science themes. Although all students participate in cohort training, it is not graded and does not count towards your PhD award.
- You start your PhD research immediately, in parallel with the training programme. The cohort training is weighted towards the first half year, so during this time you will be learning skills while developing your PhD topic.
- Network and training events, both online and face to face, will take place throughout your PhD period.
Training
In UNRISK, we offer cohort-level common skills training unique to UNRISK, wider research and careers skills training, subject-specialist knowledge and peer learning. Several weeks in the first 6 months are spent on training while you embark on your PhD, with many events distributed across later years.
- Cohort skills training covers data science and the science of decision-making and communication. Training will occur mainly in the first half-year to rapidly secure the fundamentals upon which your PhD research will be based. Three week-long residential events will progressively cover the skills needed to understand the process of (i) generating a dataset, (ii) interpreting it, and then (iii) ensuring a route to impact by using the data to assist with decision-making.
- Careers skills training is partly at cohort level and partly tailored to you.
- Subject-specific knowledge courses are chosen by you to suit your PhD, taking advantage of a large number of masters-level modules at the three universities. These courses are taken on a “sit-in” basis without assessment.
- Peer learning is a unique aspect of a CDT, with opportunities for sharing expertise during team-based learning and other activities such as peer review of articles.
- Challenge Weeks led by our partners will bring everything together and ensure that your research and training are effective in the real world.
Cohort skills training
You will develop climate science domain knowledge that is tailored to your PhD, partly through a large number of Masters-level modules available at the the three universities. In addition, all students will develop proficiency in transferable skills related to:
- Data science: Computer modelling, machine learning, digital twinning, uncertainty quantification, decision support systems, rare event modelling, model-observation fusion, forecasts and projections.
- Decision and communication sciences: Decision-making under uncertainty, how uncertainty and risk are communicated, the effect of operational constraints on the use of information, effects of uncertainty on policy development.
Why is cohort-level common training important?
Climate change is inherently multidisciplinary. While we need deep specialists like AI experts and climate modellers, you will be of higher value to an organisation and stand a greater chance of career advancement if you have some training in the whole challenge. This is what employers want – agile employees who know the science, data science, and decision landscape.
