Data Science Fellowships in Anaesthesia, Critical Care and Pain Medicine
Congratulations to Mohamed Shoair and Josie Robertson who were recently awarded awarded Data Science Fellowships. The fellowships are funded by Edinburgh Anaesthesia Edinburgh Anaesthesia Research and Education and Edinburgh and Lothians Health Foundation.
The Data Science Fellowship Scheme equips trainees in anaesthesia or intensive care medicine to learn a range of skills and tools to transform care for their patients and the health systems in which they work.
The demand for healthcare professionals with data science skills is unprecedented. Critical care and anaesthesia are data-intensive specialties. Pursuing a clinical career in Edinburgh in these areas provides opportunities to leverage data from population and clinical sources.
The Fellowship aims to equip trainees in anaesthesia or intensive care medicine to learn a range of skills and tools to transform care for their patients and the health systems in which they work. For trainees interested in pursuing an academic career, the Fellowship will enable the individual to demonstrate methodological training to compete for run-through academic training programmes (such as ECAT) and clinical PhD fellowships.
Specifically successful applicants for the fellowship will:
- Gain knowledge of the fundamentals of data science leading to a formal qualification (Postgraduate Diploma);
- Develop expertise in accessing, interpreting and integrating data-intensive research into practice; and
- Build the knowledge and skills to engage effectively with data-driven approaches to health care.
The Fellowship is aimed at trainees in anaesthesia or intensive care medicine with clear evidence of excellent progression in clinical training who have completed their primary FRCA or equivalent. Applicants will be appointed to start in September 2022.
Applicants will be in-programme trainees on the SESSA (South East Scotland School of Anaesthesia) or ICM training programme, employed through the NHS. These are not out-of-programme training posts, but are tailored to trainees interested in developing skills in data science. Clinical training programmes will continue during the fellowship, but regional training coordinators will work closely with the supervisors to ensure 30 days (at most) of protected study leave time per year is available through a flexible approach (or pro-rata for less than full time trainees).
Trainees should discuss with the relevant Training Programme Director (Anaesthesia: Dr Jeremy Morton; Critical care: Dr Neil Young) to ensure that taking up this opportunity will not impact on progression in clinical training.
Candidates are required to gain 120 credits to be awarded a PGDip. The Fellowship will fund £10,000 towards PGDip fees. Candidates are required to contribute the remainder of course fees for the PGDip.
Trainees who are interested in applying for the fellowship should send a CV and a 200 word statement to explain what you hope to gain by undertaking this Fellowship. These should be sent by email to Nazir Lone