Clinical PhD Fellow at UKRI Centre for Doctoral Training in AI for Healthcare
Applications are invited from exceptional medical graduates who demonstrate a commitment to a research career and aspire to become the next generation of AI researchers and clinical academics leaders who are driving AI-based solutions applied to healthcare. The Centre’s vision is to establish a new generation of innovators in Artificial Intelligence (AI) applied to Healthcare. Tackling healthcare challenges requires learning how to bridge...
Job listing information
- Reference ENG01105
- Date posted 23 January 2020
- Closing date 6 February 2020
Applications are invited from exceptional medical graduates who demonstrate a commitment to a research career and aspire to become the next generation of AI researchers and clinical academics leaders who are driving AI-based solutions applied to healthcare. The Centre’s vision is to establish a new generation of innovators in Artificial Intelligence (AI) applied to Healthcare. Tackling healthcare challenges requires learning how to bridge our understanding of the clinical language and methodologies, regulatory, legal and ethical frameworks of healthcare with core AI technical skills. Our training outcomes are AI researchers who have learned to move fluidly across the disciplinary AI/healthcare boundaries and can develop and implement deployable solutions. Crucially, we will empower our alumni through our unique training program to become independent actors in the highly regulated healthcare technology market and enable them to consolidate their impact through our NHS partnerships and globally through our international industrial partners so as to become part of the long-term legacy of our UKRI Centre for Doctoral Training.
Clinical PhD Fellows of the Centre AI for Healthcare will undergo a research training that has four healthcare themes that can leverage AI: (1) Making healthcare provision more efficient and effective by increasing the productivity of doctors and nurses; (2) Developing AI-based diagnostics & monitoring that can detect disease earlier and monitor health with higher precision; (3) AI-based decision support systems that will free up doctors’ time to focus on the patient or optimising the delivery or development of treatments (4) Biomedical discovery driven by AI that accelerates drug discovery and linking e.g. genome and environment data to discover novel disease mechanisms and treatment pathways.
The selected individuals will be placed within a highly supportive environment and be provided with cutting-edge research projects under expert-supervision: each doctoral researcher will have at least 1 AI and 1 clinical supervisor. The clinical supervisors and healthcare partners span the full breadth of healthcare challenges facing society, such as dementia, brain and mental health, infectious diseases, cancer and surgery, obesity and diabetes, cardiovascular and lung diseases, intensive care and primary care.
The Fellowships will be full-time and fixed-term for three years. The funding covers a clinical salary and the PhD registration fees at the UK/EU level for that time. Applicants must be a GMC-registered doctor in training in the UK, be at core training level or above, in any speciality, be eligible to take time out of their clinical training programme (OOPR). GP trainees may apply if within 12 months of having CCT.
Duties and responsibilities
Successful candidates will be selected on the basis of academic potential to reach the highest standards of scientific research, regardless of clinical speciality. Candidates must be able to present evidence of outstanding academic and research experience which fits the vision and key research areas of the UKRI Centre for Doctoral Training in AI for Healthcare.
Clinical PhD Fellows will also need to satisfy requirements as stated by the Imperial College London Graduate School (Professional Skills programme), by the sponsor UKRI (e.g. periodic reporting on progress) and by the AI for Healthcare CDT as part of their PhD research degree training and registration.
Candidates should have a medical qualification (MBBS, MM BCh or equivalent) and be a fully registered doctor (or eligible for full registration) in training in the UK. Candidates must also be at core training level or above, in any speciality, and be eligible to take time out of their clinical training programme (OOPR). GP trainees may apply if within 12 months of having CCT.
Furthermore, we expect evidence of strong skills in an AI-relevant discipline, such as computer science, engineering (mechanical, electrical/electronics, biomedical), mathematics, and physics. Please see the job description for the full set of requirements.
Candidates also need to submit an application (for the PhD registration) via the Imperial College online application portal, please. Our programme title is ‘AI and Machine Learning’.
[In the application system, please select 'Postgraduate Research' as application category first].
The PhD, as well as the job application, require a personal statement. The statement -which can be the same for both- should be one A4 page long and should describe your academic and career plans as well as your motivation and your research interests. When writing the personal statement, please ensure to answer the following questions: i) What are your machine learning interests? ii) What are your healthcare interests? iii) Why do you think the UKRI AI for Healthcare CDT is the right choice for you?
Candidates are not required to submit a project proposal. Following the application reviews and interviews, successful candidates are given access to a project pool to select projects from. Some candidates may have been in contact with a supervisor as they already have a project idea; if this is the case, please do state who you have been in contact with and what the project idea is in the application. Again, this is not a prerequisite, nor is it guaranteed that the project will be approved to be available. The position will be spread among all departments in the Faculty of Medicine.
For technical issues when applying online please email email@example.com
Closing date: 06/02/2020
To apply, visit www.imperial.ac.uk/jobs and search by the job reference ENG01105.
About Imperial College London
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