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) for engineered microbial strains. Design and implement machine learning algorithms to predict strain performance and optimise metabolic pathways. Integrate multi-omics datasets into computational workflows
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candidate will: Develop genome-scale metabolic models (GEMs) for engineered microbial strains. Design and implement machine learning algorithms to predict strain performance and optimise metabolic pathways
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machine learning model to rule out heart attacks in the emergency room, which has the potential to translate to large savings for healthcare systems in the world, (2) a computational modelling to assist in
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development, machine learning and signal processing, and system integration. We are interested in working on different areas to improve the BCI technology. These areas include (but are not limited
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About the role We are looking for a Learning Technologist to join our established digital education team to support the Faculty of Medicine with the configuration of relevant learning technology
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background knowledge in statistical genetics, machine learning, omics data analysis, and computational biology. Additional knowledge in transcriptomics, statistics, and foundation models is also desired. Fixed
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? If so, then Norland is the place for you. Our TEF Gold-rated award-winning early years undergraduate degree and integrated diploma programme is world-renowned for delivering outstanding teaching, learning
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About the project: Machine learning accelerated Inverse Design of Graphene Nanoribbons for Green Energy Supervisor: Dr Sara Sangtarash, University of Warwick Thermoelectric materials convert heat
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Learning and Teaching Administrator ( Job Number: 26000196) Department of English Studies Grade 4: - £25,844 to £26,663 per annum (pro rata) Open-Ended/Permanent - Part Time Contract Duration: N/A
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for passionate and highly motivated Teaching Faculty. The Undergraduate Division is seeking teaching faculty to teach an undergraduate course, Machines that Create, an introductory yet comprehensive overview