431 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"MPG" positions at University of Oxford
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
documents. The Supporting Statement should include a cover letter and should also clearly describe how you meet each of the selection criteria listed in the job description. Click here for information and
-
(typically 60% of working hours on-site and 40% remotely) More information about working at the School can be found on our jobs page . About the role Anchored at the Blavatnik School of Government, University
-
within the Institute. This role is suitable for individuals who hold, or will have been awarded by the start date, a PhD/DPhil in AI Ethics and/or Data Ethics and/or Neuroethics and/or Philosophy
-
systems are accurate, well maintained, and effectively support operational activities, acting as a first point of contact for users and queries. You will assist with system configuration, data quality
-
Spärck AI Graduate Scholarship Named after pioneering British computer scientist Karen Spärck Jones, the Spärck AI Scholarship programme is a government funded initiative which provides full funding
-
, collecting data on small-scale movements of the eyes during visual tasks using high-resolution in vivo retinal imaging. The post is full time for 12 months or until the grant end date of 30 June 2027
-
research projects • Analysing complex data and generating original research ideas • Publishing in high‑impact journals and presenting at international conferences • Contributing to group strategy, funding
-
the Oxford-based senior bioinformatician for computational analysis of available and emerging single-cell and spatial multiomics data from HIC samples, derived mostly from skin biopsies, and human
-
, contributing to data analysis and reporting, and helping to ensure the smooth running of research programmes. About you We are looking for someone who is proactive, organised, and collaborative, with strong
-
on research pertinent to the project. By scaling up data, compute and model size, large language models (LLMs) have gained an impressive and ever growing array of capabilities. The next phase of development