148 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"https:" positions at University of Liverpool
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A Research Coordinator position is available in the group of Professor Andrew Cooper at the University of Liverpool. The Research Coordinator will bring their expertise to strengthen the relevant
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the Institute of Systems, Molecular and Integrative Biology at the University of Liverpool. You will be responsible for applying computational methods on datasets generated from sequenced samples collected
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to enhance its position as a world-class School of Management. The Chair will sit within the Economics Group, led by Professor Giuseppe De Feo. The successful candidate will make an outstanding scholarly
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in glaciology, environmental science, computer science, data science, or related discipline that is relevant to the role. The post is available from February 2026 and is fixed term for 24 months
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Clinical Education Fellows: MBChB Programme (5 posts for August/September 2026 start, 1 post for February 2027 start). Salary is paid at current clinical salary base rate. As a resident doctor
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We are seeking a dedicated and driven Hospitality Assistant to join our dynamic team at Bertie & Bellas. About the Role As a Hospitality Assistant, you will play a key role in ensuring seamless
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projects aimed at advancing our understanding of cancer biology and improving patient outcomes. You will work with advanced technologies, pre-clinical tumour models, and patient-derived samples, contributing
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and is available on a part time basis (0.1857 FTE, 6.5 hours per week). The research assistant will be responsible for the design of the online resource based on this data to ensure that the content
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of automated workflows for the analysis of existing remote sensing data archives and potentially near-real time analysis. You will work with the Principal Investigator (Professor. James Lea) to agree a programme
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials