Sort by
Refine Your Search
-
into the ethical governance of Large Language Models (LLMs), as part of the prestigious Divirsibus Vis Plurima Solvo project. The position is full-time and fixed term for 41 months or to the funding end date of 30
-
associated with the research group of Professor Christopher Yau based in the Big Data Institute at the University of Oxford. The role will involve developing novel artificial intelligence (AI)-based methods
-
replication. This post is fixed term for 3 years. What are you going to do? In this fully-funded project, you will: • develop and employ novel advanced biophysical instrumentation based on optical
-
). The post is funded by NIHR and is fixed-term for 24 months, with a possible extension. This project is about creating novel AI models to predict patient outcomes following acceptance or refusal of an offer
-
. The research is further supported by Professor Eric O’Neill (Oncology), who leads a large research group focused on pancreatic cancer immunobiology. The role will be based across the Institute of Biomedical
-
We are seeking to appoint a highly motivated Postdoctoral Researcher with expertise in innate immune responses to cancer, in vivo/in vitro experimental models, and advanced molecular techniques
-
Based at Oxford Population Health (Nuffield Department of Population Health), the Demographic Science Unit (DSU) is at the forefront of demographic research that aids society, government and
-
Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
, epidemiology, and socio-environmental modelling. To be considered a successful candidate; A PhD degree in Ecology, Biodiversity analyses, Environmental Science, Remote Sensing, Epidemiology, Data Science, or a
-
original research on the grid integration of second life battery storage systems. The research will bring together second-life battery modelling, power system optimisation and technoeconomic evaluation
-
challenge. We seek a senior computational biologist to apply these extensive in-house datasets toward the development of novel, domain-tailored machine-learning models and analytical methods. You will explore