Doctoral Network in Artificial Intelligence for Future Digital Health is a doctoral training centre funded by the University of Liverpool from October 2019 to train the next generation of world-leading experts in Artificial Intelligence to solve data intensive problems in healthcare.
- Vision of the doctoral network
- Leadership team of the network
- PhD projects: current and future
- Cohort-based training for PhD students
Vision of the doctoral network
- The network will create a community of AI health care experts who will develop new AI tools for medical applications.
- The vision is to establish a world-class centre providing high-quality doctoral training in AI for Future Digital Health.
- The cohort-based training in a collaborative environment will feature peer-to-peer and cohort-to-cohort learning.
- Each PhD project is carefully co-created in collaboration with a health provider and/or a healthcare commercial partner.
- On completion students will be well-placed to take up rewarding careers within the domain of AI and Digital Health.
Back to Top of this page | Back to Home page
Leadership team of the network
- Prof Frans Coenen (director) supervised 50+ successful PhDs in Computer Science.
- Dr Vitaliy Kurlin (co-director, training champion) leads the TDA group in the MIF.
- Prof Katie Atkinson (recruitment) is an expert in AI and the dean of EEECS school.
- Prof Marta Garcia-Finana (equality, diversity, inclusion) is an expert in Biostatistics.
Back to Top of this page | Back to Home page
PhD projects: current and future
- Each of 11 projects below is funded for 3/3.5 years and covers the EU/UK tuition fees and a a standard PhD bursary. International candidates can be considered, but the funding can cover only international tuition fees without a bursary.
- Depending on the overall quality of candidates for all projects, very few exceptionally strong international candidates for some projects can get a contribution to partially cover their living expenses, which might be less than a 100% bursary.
- The projects below were selected through a multi-stage rigorous peer-review. Each project has two academic supervisors (from different areas) and one industry supervisor from a hospital or a commercial company working with health data.
- The deadline for applications is 28th May 2019. Here are the PhD projects for the 1st cohort from October 2019.
- Application of Artificial Intelligence systems to develop novel diagnostic and prognostic tools for hepatocellular carcinoma
- Using AI to leverage new forms of data in modelling cycling behaviours in the LCR
- Machine Learning of Epidemic Models
- An intelligent imaging technology for automatic characterisation of the refractive power of human eye
- Deep Feature Learning for Distributed Rehabilitation Robots with Wearable Tactile Sensing
- Research Objects for Palliative Care
- A study of cellular diversity in health and disease using mass cytometry
- An Intelligent Assistant for Medical Doctors when Prioritising Pathology Results
- Machine Learning for the next generation of paediatric wheelchairs
- The epidemiology of disease clusters in adults with multimorbidity
- High-precision MRI-linac radiotherapy of lung cancers: Using AI to rapidly estimate whole tumour contours from pre-treatment magnetic resonance 4D-images and real-time orthogonal slice-pair images
- Advice on applications: you could discuss your relevant skills with project supervisors listed at the pages above. I'm the second supervisor of project 7 whose first supervisor is Dr Joseph Slupsky from Molecular and Clinical Cancer Medicine.
- For any questions please e-mail the directors of the doctoral network: Prof Frans Coenen and Dr Vitaliy Kurlin.
- In any case please submit your application via the University of Liverpool webpage: how to apply for a PhD.
Back to Top of this page | Back to Home page
Cohort-based training for PhD students
- Dr Vitaliy Kurlin will lead the following cohort-based training programme in the doctoral network from October 2019.
- Students with complementary skills will be paired (possibly with more senior students) to encourage peer learning, e.g. all PhD students from the EPSRC Centre for Doctoral Training in Distributed Algorithms and TDA group are also welcome.
- The network will run the weekly 3-hour session between 11.00-14.00 for all PhD students in the network as follows.
- The presentation at 11-12 will be based on a taught module in Data Science or will be given by an external speaker.
- The lunch at 12-12.30 will be provided for free, but should be well-deserved by an active participation in the network.
- The moderated workshop at 12.30-14.00 is for students to present and discuss their solutions to practical exercises.
- The relevant modules are Introduction to Data Science (term 1), Geometric and Topological Data Analysis (term 2).
Back to Top of this page | Back to Home page