Combined MSc & PhD programmes (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 will commence in September 2019 (and 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 (BioMedAI) at Edinburgh is led by Professor Guido CDT Sanguinetti, who is supported by an interdisciplinary programme team from the School of Biological Sciences, the MRC Institute of Genetics and Molecular Medicine, the Usher Institute of Population Health Science and Informatics, and the School of Social and Political Sciences.
The UKRI CDT in Biomedical AI delivers an interdisciplinary training programme covering technical AI skills, biomedical foundations and individually tailored training on understanding the societal aspects of Biomedical AI.
Modern data gathering technologies enable us to observe multiple aspects of disease processes at vastly different organisational scales and the core vision of the CDT is that AI technologies will be a key driver in furthering our understanding and discovering actionable interventions in biomedicine.
The CDT in BioMedical AI is a 1 + 3 programme; students will complete a 1 year an MScR programme and then transfer into a 3 year PhD programme on successful completion of the MScR.
Natural Language Processing
The UKRI CDT in Natural Language Processing (NLP) at Edinburgh is led by Professor Mirella Lapata and Dr Adam Lopez.
The programme brings together researchers in NLP, speech, linguistics, cognitive science, and design informatics from across the University of Edinburgh.
Students benefit from cutting edge computing and experimental facilities, including a large GPU cluster and eye-tracking, speech, virtual reality, and visualization labs.
The CDT involves over 20 industrial partners, including Amazon, Facebook, Huawei, Microsoft, Mozilla, Reuters, Toshiba, and the BBC. Close links also exist with the Alan Turing Institute and the Bayes Centre.
The CDT NLP is a 4 year PhD with integrated studies. The degree program is designed to be maximally flexible, while also including some compulsory taught courses at level 11 and above.
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.
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.
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.
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.