DRIVE-Health PhD Programme
We have completed our first round of recruitment for the Centre for Doctoral Training in Data-Driven Health. We are now accepting the second round of applications for the 2020 intake, which is restricted to projects with already secured industrial funding.
Overview
We are looking to recruit outstanding graduates from a variety of backgrounds to a 3.5 year (or 3 year depending on funding source) PhD programme in Data-Driven Health to work on internationally-competitive research projects, equipping them to exploit excellence in medical and informatics research for improving the health of local and national patient populations; this call is for applications for PhD studentships for October 2020 entry. Students will benefit from multi disciplinary supervision and opportunities for visits to our international partners.
DRIVE-Health studentships offer a generous stipend of £17,520 per annum for the 2020/21 academic year. The Centre for Doctoral Training (CDT) will also provide funds for research project support – travel, conferences, etc.
Costs for PhD fees (UK/EU applicants) are covered by the CDT. We also have a limited number of full fee waivers for international applicants. We welcome applications from international applicants if they are able to top up the fees themselves.
Visit fees and funding webpages to find out more about bursaries, scholarships, grants, tuition fees, living expenses, student loans and other financial help available at King’s.
Academic Requirements
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Application & Enquiries
Please apply via the King’s Apply website to the Programme: “DRIVE-Health: Centre for Doctoral Training in Data-Driven Health (MPhil/PhD)”.
For queries and suggestions for new project ideas please contact drivecdt@kcl.ac.uk in the first instance, who may put you in touch with a theme lead or an appropriate supervisor. All projects are list below.
Entry Requirements
English Language Requirements (Band D)
Based on the IELTS test scoring system, this programme requires that successful candidates achieve the following level of English before enrolling. Successful applicants’ offer letters will include information about when they must have achieved this standard.
- Overall: 6.5
- Listening: 6
- Speaking: 6
- Reading: 6
- Writing: 6
Visit our admissions webpages to view our English language entry requirements.
Personal Statement and Supporting Information
You will be asked to submit the following documents in order for your application to be considered:
- Personal Statement (Yes)
A personal statement is required. This can be entered directly into the online application form (maximum 4,000 characters) or uploaded as an attachment to the online application form if you have a longer personal statement (maximum 2 pages). Please include your top 3 project preferences in your personal statement. - Research Proposal (Yes)
You are not allowed to submit your own project proposal for this second round of application. Please simply duplicate the project preferences in the research proposal section, all the projects are list below. Maximum upload file size: 3MB. - Previous Academic Study (Yes)
A copy (or copies) of your official academic transcript(s), 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. - Reference (Yes)
Reference is required as part of an application. You can fill in the details of your referee into the online application form.
When you submit your application, your referee will be sent a link to our King’s Referee Portal, where they can provide a reference.
We will not accept references from personal email addresses (e.g. yahoo, hotmail, gmail or other similar public systems) and we are unable to accept references from family members or friends. Please use your referee’s official, professional email address. - Other (Optional)
You may wish to include a CV (Resume) or evidence of professional registration as part of your application.
Funding
If you are applying for our DRIVE-Health Studentship, please tick “5. I am applying for a funding award or scholarship administered by King’s College London” in the funding section, and fill in the Award Scheme Code or Name box with “DRIVE-Health Studentships” inside the Award Scheme Code or Name box.
Important Dates
The closing date for applications under this scheme is Friday 14th August 2020, 5pm British Summer Time (UTC+1). Interviews for shortlisted candidates have been provisionally scheduled for mid-August 2020. Successful applicants are expected to take up their studentships in October 2020.
List of Projects for the Second Round of Recruitment for 2020 Intake
| ID | Project Title | Lead Supervisor | Co-supervisor(s) |
|---|---|---|---|
| 15 | Deep learning for risk stratification of patients with liver cancers | Julia Schnabel | Cheng Fang |
| 18 | Use of machine learning and clinical phenotyping to identify determinants and predict CVMD risk using data from registries and electronic medical records | Vasa Curcin | Abdel Douiri, Jorge Cardoso, Mark Ashworth, Andrew Krentz or Richard Barker |
| 19 | Advancing explainable human in the loop NLP analytics for clinical applications | Iain Marshall | Angus Roberts, Petr Slovak, Serge Umansky |
| 21 | Emulating trials using EHR and Cogstack | Sabine Landau | James Teo, Richard Dobson, Dan Bean |
| 32 | Stroke prevention in patients with atrial fibrillation (AF) and co-morbid physical and mental health problems | Fiona Gaughran | Mark Ashworth |
| 34 | A whole-genome sequencing approach to advance precision medicine and study patient heterogeneity | Ammar Al-Chalabi | Alfredo Iacoangeli |
| 47 | Using multi-omic data for neuroendocrine cancer diagnostics and metastatic predictions | Rebecca Oakey | Cynthia Andoniadou, Louise Izatt |
| 64 | Optimising the management of patients with respiratory illness including influenza and COVID-19 in emergency and acute pathways | Yanzhong Wang | Vasa Curcin, Jonathan Edgeworth |
| 66 | Using machine learning to understand multimorbidity progression and its prognostic impact in patients with heart failure | Zina Ibrahim | Rosita Zakeri, Rebecca Bendayan, Andrew Cooper |