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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations to biomolecular systems is a plus but not required. Applicants
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QUALIFICATIONS Education: PhD or Doctorate degree Medicine (MD) required Experience: No previous experience required Knowledge, Skills and Abilities: Learning Agility: Ability to learn new procedures, technologies
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qualification, you must hold a PhD degree (or equivalent) in computer science, computer engineering, or electrical engineering. Hardware design in a hardware description language such as Chisel, VDHL, or Verilog
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization
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projects and publications from the group can be found here: https://www.kcl.ac.uk/research/pavri-group About the role The project is focused on combining artificial intelligence (AI)-based machine learning
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analysis; Biomarker identification through the use of machine learning approaches; and Multi-omics data integration with genomics, transcriptomics and methylomics data. Job Description Primary Duties
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Experience with molecular biology techniques and cell culture Willingness to learn new techniques and skills Ability to independently design and conduct experiments Willingness to think critically A passion
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. Responsible and dependable with attention to deadlines and skills in time management. Motivated, creative, and ready to learn new things. Skill in handling multiple competing priorities. Specialized skills in