Training Programme

NUdata CDT students will experience a high-quality research training environment with a cohort-approach to training focused on the student experience. Students will undertake an original research project, which brings together big data skills and expertise from STFC’s remit (primarily in the areas of planetary, solar physics, heliospheric physics, stellar physics, galaxies, cosmology or particle physics). During their PhD, NUdata students will publish their research in high-impact journals (supported through writing workshops and close mentoring from the academic team) and present their research at conferences to a range of academic beneficiaries. In other words, they will experience the same high-quality training environment and access the general training opportunities as our other PhD students in this area.

However, in addition to this, there are three key features of our CDT:

  1. Students will receive specific training on data intensive science techniques (a formal assessable programme – see below),
  2. Additional training in transferable skills on a cohort basis (including innovation and industrial practices), and
  3. At least six months of each studentship will be spent outside the centre in one or more organisations engaged in the development and/or use of data intensive science techniques.

Upon graduation our students will have the distinct privilege of choosing whether they become leaders in academia or industry.

NUdata students will be formally enrolled at either Northumbria or Newcastle – depending on where their principal supervisor is based – and this will give them a home institution. However, the students will be part of a cohort that has all their formal training together. The cohort will take Data Science classes together, with some courses on Newcastle’s campus and some on Northumbria’s campus (the Northumbria and Newcastle campuses are within 500m).

Formal programme of taught coursework

NUdata will provide a structured cohort-based training programme in which, for the first 8 months, students undertake a formal programme of taught coursework. The modules will be drawn from a subset of modules of the pre-existing MSc Data Science degrees at both institutions.

The modules that you will study are:

  1. Principles of Data Science
  2. Machine Learning
  3. Deep Learning
  4. Bayesian Data Analysis

This programme of taught modules is specifically designed to give you a broad and thorough grounding in computational techniques and other issues relating to big data challenges.

Additional Training in Transferable Skills

Students will take part in a variety of other skills-based and transferable training. The CDT programme consists of core training modules taken by all NUdata candidates, including specific training in Equality, Diversity and Inclusion (EDI), Responsible Research and Innovation (RRI), Innovation (including translating research into a successful product), project management, as well as bespoke group projects targeting the needs of industrial partners.