340 machine-learning-"https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" positions at University of Oxford
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
We are seeking to appoint a Monitoring, Evaluation and Learning Lead within the Pandemic Sciences Institute. You will be responsible for providing expert leadership on monitoring, evaluation and
-
biology/bioinformatics, statistics, machine learning or related field. You will have a strong track record of applying genetics-based, physicochemistry-based and structure-based computational or statistical
-
machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. What We Offer As an employer, we
-
spectroscopy methods (Operando XPS/XAS, Hard XPS) to probe the interfacial reactions occurring in Li-ion batteries. Further information about the research group can be found at: https://emi.materials.ox.ac.uk
-
). The successful candidate will work in Dr Ruxandra Dafinca’s team ( https://www.ndcn.ox.ac.uk/team/ruxandra-dafinca ) in a stimulating environment as part of the Nuffield Department of Clinical Neurosciences and
-
pages on the application process at https://www.jobs.ox.ac.uk/application-process The closing date for applications is 12:00 midday on 29 April 2026.
-
) Further information can be found at http://www.eng.ox.ac.uk/jobs/home Only online applications received before midday on 8 May 2026 can be considered. You will be required to upload a covering letter
-
guidance at https://www.jobs.ox.ac.uk/cv-and-supporting-statement. Any technical questions related to this vacancy can be sent to: recruit@ouce.ox.ac.uk The closing date for applications is 12.00 noon on 7
-
Policy online course, which is FCDO’s flagship learning offer. The course aims to provide learners with a clear understanding of important economics concepts relating to foreign policy, development, and
-
3.5-year D.Phil. studentship Supervisors: Prof Noa Zilberman The training of new AI models, as well as their deployment for inference, is transforming the design of computer networks. In