School of Informatics

Centres for Doctoral Training (CDTs)

The School of Informatics is involved with five UKRI / EPSRC Centres for Doctoral Training.

New CDT Programmes

We are delighted to announce that the School of Informatics was successful in their bids for two new CDTs - Biomedical Artificial Intelligence (BioMedAI) and Natural Language Processing (NLP).  The first cohorts commenced in September 2019 and will continue until September 2023. 

More details on these CDTs and guidance on how to apply are provided below.

Biomedical Artificial Intelligence

The UKRI CDT in Biomedical Artificial Intelligence is led by Dr Ian Simpson at the School of Informatics and supported by an interdisciplinary programme team from the School of Biological Sciences, the Institute of Genetics and Cancer, the Usher Institute of Population Health Science and Informatics, and the School of Social and Political Sciences.

The CDT offers an interdisciplinary training programme covering technical AI skills, biomedical foundations and individually tailored training on understanding the societal aspects of Biomedical AI.

CDT students will benefit from access to a unique breadth and depth of expertise, as well as state-of-the-art computational and experimental facilities. Additionally, leading clinical, industrial and international academic partners will provide students with opportunities for hands-on application in a broad variety of contexts.

The CDT in Biomedical AI is a 1+3 programme: students will complete a 1-year MScR training programme and then transfer to a 3 year PhD programme to pursue an interdisciplinary PhD project under the joint supervision of an AI expert and an application domain expert. The programme is fully funded for 4 years, covering tuition fees, stipend at UKRI level and an allowance for travel/research costs.

BioMedAI website

Application, fees and funding information 

Natural Language Processing

The UKRI CDT in Natural Language Processing (NLP) brings together researchers in NLP, speech, linguistics, cognitive science, and design informatics from across the University of Edinburgh. It is led by professor Mirella Lapata and a research team from Informatics and the School of Philosophy, Psychology & Language Sciences.

Students benefit from cutting edge computing and experimental facilities, including a large GPU cluster and eye-tracking, speech, virtual reality, and visualisation labs.

The CDT involves over 20 industrial partners, including Amazon, Facebook, Huawei, Microsoft, Mozilla, Naver, Toshiba and the BBC.  Close links also exist with the Alan Turing Institute and the Bayes Centre.

The CDT NLP is a four year PhD with integrated studies.  The degree programme is designed to be maximally flexible whilst also including some compulsory taught courses at level 11 and above.

NLP website

Application, fees and funding information

Application & degree programme table

Robotics and Autonomous Systems (RAS)

The EPSRC CDT in Robotics and Autonomous Systems (RAS) at Edinburgh is led by Dr Michael Mistry (Edinburgh) and Professor Helen Hastie (Heriot Watt University, Edinburgh).

The Centre addresses key challenges for managing interactions between robots and their environments, between multiple autonomous systems, and between robots and people.

As with the other CDTs, the centre uses industrial engagement to ground research and training on real world challenges, enabling an innovation pipeline from research to global markets.

The centre is supported by Edinburgh’s world class infrastructure in robotics.

Robotics and Autonomous Systems website

Application, fees and funding information

Current student's blog post about being a robotics CDT student

Ongoing CDT Programmes

These centres admitted their final funded cohort in the 2018/19 academic year. These two Centres have a large cohort of students working in their specialist areas of Data Science and Pervasive Parallelism.

Data Science

Edinburgh hosts the EPSRC CDT in Data Science, led by Prof Amos Storkey and Dr Adam Lopez in the School of Informatics.

Data Science focuses on the computational principles, methods, and systems for extracting knowledge from data.

Large data sets are now generated by almost every activity in science, society, and commerce, ranging from molecular biology to social media, from sustainable energy to health care.

Data science seeks to efficiently find patterns in these vast streams of information.

Data Science website

Pervasive Parallelism

The EPSRC CDT in Pervasive Parallelism is led by Professor Mike O'Boyle in the School of Informatics.

It seeks to address the end of the one-step-at-time era of sequential computing.

Students focus on systems containing multiple processors.

Their research reconsiders how to design programming languages and architectures, for example to allow flexible trading of energy for performance.

Researchers also consider the necessary theories and methodologies to reason about the behaviour of this new hardware and software.

Industrial interaction ensures that students engage with real world case-studies.

Pervasive Parallelism website

Related links

Virtual tour of the Informatics Forum