35 phd-studenship-in-computer-vision-and-machine-learning PhD positions at University of Cambridge
Sort by
Refine Your Search
-
community of researchers who conduct cutting-edge research into NLP and AI within the University of Cambridge. Appointment at Research Associate level is dependent on having a PhD (or equivalent experience
-
language processing (NLP), large language models (LLMs), machine learning (ML), and data visualization. The candidate will leverage their expertise in AI, statistics, and programming to design, develop, and evaluate
-
of the project is to 1) develop computational pipelines for image analysis and physical analysis of cell shape trajectories, and for combined morpho-molecular analysis of cell shape together with molecular markers
-
deliver world class turbine testing at TRL 6 level in the Whittle Laboratory's new National Centre for Propulsion and Power. This will require you to create and execute engineering design, computational
-
The GOdogs group is looking to appoint researcher to our group which studies the genetics of obesity, starting with canine genetics but with a strong programme of allied human comparative genetics
-
in patient samples. We are a multidisciplinary team of molecular and functional lab scientists, computational biologists, and clinical fellows. The successful applicant will be integrated within a
-
of transposon-derived variation and its role in functional genetic variation and genome evolution in animals. A PhD in a biological science or computational science is essential for this role. Those who have
-
obtaining) a PhD in Engineering or other relevant area Knowledge and experience in: Material flow analysis, environmental assessment, emissions accounting or other topics and tools of Industrial Ecology
-
A PhD is desirable but not required. Other industry, city government or research experience that demonstrates the capability to produce independent original research is also desirable. Very good
-
suited to candidates with strong quantitative and analytical skills and a PhD (or near completion) in cancer epidemiology or a related field. Applicants should have experience in applying or developing