Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
. This role is eligible for sponsorship under the skilled worker route. Commitment to Diversity The University of Liverpool is committed to enhancing workforce diversity. We actively seek to attract, develop
-
increased to Grade 7, spine point 31. Commitment to Diversity The University of Liverpool is committed to enhancing workforce diversity. We actively seek to attract, develop, and retain colleagues with
-
of Liverpool is committed to enhancing workforce diversity. We actively seek to attract, develop, and retain colleagues with diverse backgrounds and perspectives. We welcome applications from all genders/gender
-
Laboratory in the ‘Digital Innovation Facility’ at the University of Liverpool. You will possess, or be close to completing, a PhD in Electrical Engineering / Electronics / Computer Science or a relevant
-
Parr , alongside Dr Greg Wood , and Dr Richard Mills . The team is further supported by collaborators from Brunel University, Imperial College London, Liverpool John Moores University, Florida State
-
modelling efforts. Duties include running and analysing experiments, developing and conducting individual and collaborative research objectives, proposals and projects. The role holder will be expected
-
Cycle to Work Schemes and subsidised local bus travel Subsidised sports membership, reduced tuition fees on degree programmes for staff, access to training and development opportunities including LinkedIn
-
may be asked to assist in the supervision of student projects, the development of student research skills, provide instruction or plan/deliver seminars relating to the project research. The successful
-
. The postholder will develop, refine, and execute imaging analysis pipelines, both independently and in conjunction with other data, such as clinical outcomes, to establish meaningful relationships. Analysis
-
About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with