Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
About the role We are seeking a Programme Manager to join the Department of Engineering Science (central Oxford). The role is being offered full-time or part-time (22.5 hours a week would be
-
social mobility and its relationship to economic inequality. The post holder will work with the INET Oxford programme on Economics, Inequality, and Opportunity. About you You have completed a doctorate in
-
cell signalling pathways and demonstrate experience in integrating computational and experimental approaches to address key biological questions. Experience in supervising junior researchers and
-
the Department of Engineering Science’s Student Administration Team with a strong link to the Oxford Robotics Institute’s (ORI) Administration team. You will lead and manage the set up and academic administrative
-
multidisciplinary team approach to cardiovascular research. The research programme will involve collaboration with researchers from UK-wide centres under the leadership of Oxford and Leeds. We are looking for a
-
new collaborations within the centre. You must hold a PhD (or near completion) in statistical genetics, functional genomics, computational biology, or a related field together with proficiency in
-
discovery science where we reassemble physiological processes at the molecular, cellular, tissue and systems level of organisation. In so doing we provide a bridge to translational medicine, and interface
-
Biostatistics, Mathematics, Statistics, Computing, Mathematical Biology or a related subject. You will have expertise in making sense of microbial genetics. Proficiency in a high-level programming language is
-
the supervision of the Senior Academic Administration Officer. In addition, you will support the NDCN Academic Administration team with the Year 5 undergraduate programme when required. You will also carry out
-
applications. Applications are sought from across a diverse set of disciplines under the Information Engineering umbrella, including, for example, physics-informed machine learning and AI, computer vision