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Field
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collaborate with a diverse team of clinicians, data scientists, and industry partners to integrate cutting-edge algorithms into clinical workflows. Your responsibilities will include designing and optimizing
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focuses on the DNN model optimization and deployment in an attempt to democratize the use of generarative AI by reducing the cost of its use through a reduction on their computational requirements as
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reducing waiting lists. This will be achieved through the following objectives: Acquire data and expert-based evidence and optimise data augmentation to ensure optimal hospital patient pathways through pre
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for their expression in plant colonizing bacteria and integrating them into the chromosomes of appropriate chassis. Control systems will be designed to restrict expression to target plants and ensure optimal expression
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from outstanding candidates with expertise in Operations Research, Management Science and Business Analytics with a focus on fundamental research in combinatorial and stochastic optimization for business
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, stochastic optimization, modern machine learning methods, scalable algorithms for advanced Machine Learning techniques and explainable AI.In teaching, the position will contribute, inter alia
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peptides on cognitive functions, functional joint health, osteoporosis, and their optimal dosage. You will work at the exciting interface between clinical data collection and sports and nutritional research
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assessments of need and identify optimal solutions. Further particulars are included in the job description. The post is full time 35 hours per week, 1 FTE and permanent In line with LSHTM’s hybrid working
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., LLMs). Familiarity with MLOps practices like model registries and drift monitoring. High-Performance Computing (HPC): Strong command of Slurm or PBS, GPU optimization with ability to scale distributed
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from outputs based on expert knowledge in area of practice. This role demands a high level of expertise in both public and on-premises cloud environments, focusing on creating, managing, and optimizing