448 associate-professor-computer-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in United Kingdom
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-linear systems of ordinary differential equations and the proficient use statistical programming languages (R, Julia or Python), Bash computing and the development of computational packages are essential
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clinical trials, and developing personalised models to understand therapy response characteristics. You will contribute to a pioneering tissue-focused research programme aimed at enhancing cure rates
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, applied/medical statistics, bio/medical engineering, health data sciences, health informatics, computer science, clinical artificial intelligence, environmental epidemiology, climate data sciences, remote
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by ATi/Innovate UK and Rolls Royce and is fixed-term to June 2029. You will join a world‑leading programme advancing experimental and numerical methods to predict the impact performance of composite
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This 36-month postdoctoral position is part of the project ENLIGHT (Enabling a Lifecycle Approach to Graphite for Advanced Modular Reactors) consortium, a £13.2 million, five-year programme
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Institute is also a member of Stonewall’s Diversity Champions programme. The John Innes Centre is a registered charity (No. 223852) grant-aided by the Biotechnology and Biological Sciences Research Council.
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, stimulating, diverse research environment and actively promote a family friendly workplace. The Institute is also a member of Stonewall’s Diversity Champions programme. The John Innes Centre is a registered
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to develop a personal research programme in observational or theoretical cosmology, with a particular emphasis on ultra-large-scale cosmology (including primordial non-Gaussianity and horizon-sized effects
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characterisation programme as a postdoctoral researcher. The ability to think outside the box with creativity, along with having the drive and ambition to develop those ideas in a highly experimental laboratory is
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly