Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
Division/Team: Division of Informatics, Imaging & Data Science Hours Per Week: Full Time (1FTE) Closing date (DD/MM/YYYY): 30/07/2025 Contract Duration: 36 Months School/Directorate: School of Health
-
Epidemiology to grow capacity in the development and delivery of teaching in Health Data Science and Health Informatics. This is a fantastic opportunity for the individual to join a growing education team that
-
Digitalisation: Rethinking AI for Just and Sustainable Futures programme. There is flexibility between working 0.2 FTE, up to 0.5 FTE. This is a fixed-term post where funding is available for 12 months in
-
Digitalisation: Rethinking AI for Just and Sustainable Futures programme. There is flexibility between working 0.2 FTE, up to 0.5 FTE. This is a fixed-term post where funding is available for 12 months in
-
. About You – You should be a graduate who has a degree in Biology or Biomedical Science or Medical Sciences or similar STEM subject, is able to work independently and be self-motivated, whilst being a
-
directly with the program lead, Prof Rose McCab, Dr Alexandra Bakou (Trial Manager) and Maria Long (Trial Manager) in the School for Health Sciences, City, University of London.. The post will be based
-
: Rethinking AI for Just and Sustainable Futures programme. CFI is a highly interdisciplinary research centre addressing the challenges and opportunities posed by artificial intelligence (AI). Funded by
-
: Rethinking AI for Just and Sustainable Futures programme. CFI is a highly interdisciplinary research centre addressing the challenges and opportunities posed by artificial intelligence (AI). Funded by
-
criteria in the application statement when you apply. Essential criteria Current student or graduate in Computer Science, Software Engineering or a related discipline (assessed at: application/interview
-
, purification and biophysical characterisation. You will work within a dynamic and collaborative research group investigating protein structure-function relationships, supporting fundamental science a with real