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demonstrated expertise in AI and machine learning, including experience building and evaluating models in frameworks such as PyTorch, and running workflows in HPC environments experience applying machine
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convergence of high-performance computing (HPC) and AI, which is a subject that sees an increasing importance due to the widespread use of AI and in particular machine learning (ML). As today’s mainstream AI/ML
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events and in machine learning for the earth system is required Strong and demonstrated programming skills are required Prior experience with geospatial data analysis in Python, working on scientific HPC
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”. The project involves extensive discrete element modelling of clay using YADE on the Nottingham HPC. It will expose origins of continuum parameters for the primary clay minerals in London clay by performing
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is highly preferred. • Systems: Experience running experiments on HPC clusters or cloud environments. • Documentation: Ability to use LaTeX and scientific writing tools for technical reporting
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-performance computing (HPC) clusters or cloud GPU instances. Analytical Rigor: Ability to design ablation studies to isolate the impact of individual loss components. Communication: Ability to clearly
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cardiometabolic disease Track record of peer-reviewed publications relative to career stage Experience with multi-omic data integration Familiarity with HPC or cloud computing environments Monday through Firday
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”. The project involves extensive discrete element modelling of clay using YADE on the Nottingham HPC. The project will expose origins of continuum parameters for the primary clay minerals in London clay by
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, workflow management (Snakemake), or HPC environments is a plus. Strong analytical and problem-solving skills, with attention to detail. Excellent communication and teamwork skills, with ability
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background in cancer biology and genomics research. · Experience working with high-performance computing (HPC) environments and version control systems such as Git. · Excellent written and verbal