Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
-
Field
-
join a thriving network of researchers with mixed backgrounds, based in the University of Cambridge. The award includes Gross Salary according to EU guidelines for Marie Sklodowska Curie trainees
-
£19,000 per year. Applications for this PhD studentship should be submitted via the University of Cambridge Applicant Portal by clicking the 'Apply' button above, with Professor Duncan McFarlane identified
-
£19,000 per year. Applications for this PhD studentship should be submitted via the University of Cambridge Applicant Portal www.graduate.study.cam.ac.uk/courses/directory/egegpdpeg , with Professor Duncan
-
, post-docs and interns collaborating across universities to build better algorithms, software tools and benchmarks to assess the safety of AI implementations at the software and hardware level. We
-
undertake independent research aligned with the goals of the project, under the guidance of leading researchers, Dr James Saunderson (Monash University) and Professor Hamza Fawzi (University of Cambridge
-
microscopy Academy Research Fellow: Nian Wu (Google Scholar ) Research mobility: University of Cambridge (UK), Universidad Autonoma de Madrid (Spain), Peking University (China), National University of
-
before the end of 2025. The candidate will be based in the Department of Aeronautics at Imperial College London but will also interact with colleagues at the University of Cambridge and at the Edinburgh
-
quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel
-
for the Future of Intelligence (CFI). The candidate will contribute to teaching and lead a research programme in one or more of the following areas: ethical use of machine learning, AI safety, algorithmic
-
, at the University of Cambridge, UK. The Research Assistant will work together with a team of students and research collaborators on the development of learning-based control policies that facilitate