Sort by
Refine Your Search
-
and disease and apply this knowledge to the development of new and innovative clinical practise, alongside providing a rigorous academic programme for students. About the role Dr. Seaborne’s group
-
24 Dec 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Biological sciences Computer science Mathematics Researcher Profile Recognised Researcher (R2) Established
-
United Kingdom Application Deadline 4 Jan 2026 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
-
Application Deadline 14 Dec 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
-
) Country United Kingdom Application Deadline 19 Jan 2026 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
-
United Kingdom Application Deadline 4 Jan 2026 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
-
. The successful candidate will work within a multidisciplinary team to unravel the metabolic drivers of HCC biology and transplant rejection through cutting-edge spatial multi-omics and computational metabolic
-
(R3) Country United Kingdom Application Deadline 22 Dec 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
-
United Kingdom Application Deadline 2 Dec 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
-
University (USA), and Google Deepmind (London). About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for