Do you want to make a difference in digital advancements of healthcare? Do you want to bridge the gap between healthcare domain-based knowledge, state-of-the art computing, and personalization techniques? Do you want to test your skills in real-life healthcare applications?

Join our Center for Doctoral Training (CDT) in Digital Twins for Healthcare (DT4Health) at King’s College London!

DT4Health is an innovative PhD program located at King's, in the heart of London, arising as a joint forces collaboration between the Healthcare Faculties and the Faculty of Natural, Mathematical & Engineering Sciences.

Our mission is to train the next generation of leaders in healthcare technology to improve healthcare systems in the UK in a period of aging population and tightening financial constraints, using the cutting-edge framework of Digital Twins.

Leadership team

Projects

The program provides a cohort-based education built around individually focused research projects. Individual projects help build deep expertise and create value, while the cohort-based approach enables knowledge exchange across areas and trains students in inter-disciplinary work and communication.

Visit the DT4Health project page to find the full project portfolio for students starting in October 2023.

How to apply

DT4Health is a technology-driven CDT that aims to build multidisciplinary bridges to clinical specialities. The CDT welcomes applications from outstanding candidates from a variety of backgrounds, who are enthusiastic about multi-disciplinary research and training to build the next generation of Digital Twins in healthcare. Applicants should hold/be predicted a 1st class or upper second-class degree in relevant core subjects such as mathematics, mechanical, electronic, electrical and information engineering, computer science, physics, statistics, data science, artificial intelligence.

Each studentship is fully funded for 3.5 years. This includes tuition fees, stipend and generous project consumables.

• Stipend: Students will receive a tax-free stipend at the UKRI rate (£19,668 for AY 2022/23) as a living allowance.
• Research Training Support Grant (RTSG): A generous project allowance will be provided for research consumables and for attending UK and international conferences.

Eligibility: We welcome applications from both Home and International applicants. Please note that we have a very limited number of international studentships.

International candidates will be required to provide a certificated proof of competence in English. Please see more information on English Language requirements webpage. Our programme falls under Band D.

           Apply:

1. Have a look through the available projects that we have on offer. As part of your application, you will be asked to list three projects in order of preference. Please note that this list is for indicative purposes only and project preferences are not guaranteed.
2. Submit an application for the following programme: “DT4Health: Centre for Doctoral Training in Digital Twins for Healthcare” using the Admissions application portal via King’s Apply. You will need to register an account to log onto the system.

   Please ensure to complete the following sections of the application with all relevant information:

   • Personal Information (including Contact Information, Equal Opportunities and Fee Status). Please note that the diversity monitoring questions will not be shared with the selection panel.
   • Previous Academic Study: a copy of your official academic transcripts, showing the subjects studied and marks obtained. If you have already completed your degree, copies of your official degree certificate will also be required. Applicants with academic documents issued in a language other than English, will need to submit both the original and official translation of their documents.
   • Employment history: you will be able to enter up to five sets of employment information. Please upload a PDF copy of your CV as an attachment to the Employment History Section, even if you do not have any employment information to provide.
   • Supporting statement: please upload a PDF copy of your personal statement in this section, using this  provided template indicating three projects of interest, in order of preference from our available projects. However, please bear in mind that this list is for indicative purposes only;
   • References: Please insert contact details for two academic referees or relevant employers in research institutions/companies. Admissions will then contact your referees directly.
   • Funding: please choose Option 5 “I am applying for a funding award or scholarship administered by King’s College London” and under “Award Scheme Code or Name” enter CDT_DT4Health. Failing to include this code might result in you not being considered for this funding scheme.                                                                                                                        

   Next steps:

3. Applications submitted by the closing date will be considered by the CDT and shortlisted applicants will be invited to submit a 10-minute pre-recorded presentation. We will contact shortlisted candidates with information about this part of the assessment process.
4. The CDT will review the presentations submitted and successful candidates will be invited to attend an interview.

For any questions about the recruitment process please email us at DT4Health@kcl.ac.uk

Research

The complexity of our healthcare systems, the fascinating and intricate mechanisms of human pathophysiology, the societal, ethical, and regulatory barriers in the adoption of new technologies, and the intrinsic difficulty in the development of trustworthy solutions, are some of the challenges which we tackle through this CDT.

Digital Twin technologies provide a pathway to more efficient, data-driven, personalised, and preventive healthcare. A Digital Twin is a computational replica of a physical entity, continuously updated through time, to inform decisions. In healthcare, we can twin

• individual patient’s physiology, such as the cardiovascular system;
• an asset, for example a robotics entity or drug manufacturing facility;
• or a healthcare organization, such as the oncology department in a hospital.

Key to Digital Twin technologies is the unprecedented computational ability to support human decision making, with both inductive reasoning from data, using machine learning techniques, and deductive mechanistic modelling. The continuously optimized pairing of induction and deductions, aimed to be used in decision making, forms a Digital Twin.

Training 

DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare. By establishing a strong, interdisciplinary, and inter-sectoral training network, we educate researchers and practitioners to have both a focused speciality and the ability to bridge between diverse disciplines and three core subject areas:

• Mathematical foundations: building a Digital Twin requires continuously matching inductions and deductions from data. Our students learn and advance mathematical mechanistic models of healthcare systems, and the statistical theory for personalizing these models, quantifying the inherent uncertainty and allowing forecasting.
• Engineering technologies: updating a Digital Twin requires acquiring new data and integrating multiple data streams in large-scale simulations. Our students learn about state-of-the-art sensing and imaging technologies, and how to exploit the unprecedent computing capacity that is available nowadays to run model inferences and help decision making. DTs are complex cyber-physical systems and our students will learn how to engineer these from a software and systems perspective.
• Medicine: Our students develop a deep understanding of key concepts of human physiology, specific problems in the management of disease, and the actual needs and limitations of our healthcare system.

We also provide our students with a set of horizontal skills and targeted commercialisation workshops coordinated with the KCL Centre for Doctoral Studies. The specific selection of training events is determined based on an individual annual training-needs review undertaken by the student in consultation with their supervisory committee. Students have the opportunity to undertake a collaborative mini-project with other students crossing knowledge areas.

The program provides a cohort-based education built around individually focused research projects. Individual projects help build deep expertise and create value, while the cohort-based approach enables knowledge exchange across areas and trains students in inter-disciplinary work and communication.