Sort by
Refine Your Search
-
, world-leading AI & technology companies, together with premier biotech companies, with the overarching aim to fast-track major scientific breakthroughs, revolutionise maternal and early childhood health
-
and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
-
are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge engineering, linked data, web technologies. About the role
-
scientists across six distinguished Healthcare organisations, world-leading AI & technology companies, together with premier biotech companies, with the overarching aim to fast-track major scientific
-
this role. The role offers opportunities to engage in interprofessional or complex clinical simulation, participate in educational evaluation or research, and apply educational technology and automation tools
-
About us The Department of Chemistry in the Faculty of Natural, Mathematical & Engineering Sciences (NMES) is a friendly and growing department seeking to recruit a full-time Senior Business
-
, participate in educational evaluation or research, and apply educational technology and automation tools to enhance resource management and delivery. Candidates with experience in these areas will have the
-
geography/remote sensing, ecology, statistics, engineering, quantitative social sciences, or a related discipline. Experience in developing models and mapping with real world data, with strong programming
-
this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in spatial epidemiology, quantitative geography/remote sensing, ecology, statistics, engineering
-
and experience: Essential criteria PhD in applied mathematics, statistics, engineering, computational biology, econometrics, or a related discipline. Experience in developing complex models using real