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pension scheme 38 days annual leave A comprehensive range of childcare services Family leave schemes Cycle and electric car loan schemes Employee Assistance Programme Membership to a variety of social and
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responsibility for carrying out research in rough path theory, machine learning, generative AI and related fields as part of the DataSig II grant “High order mathematical and computational infrastructure
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,(e.g. bioinformatics, computational genomics) and have Machine learning, and bioinformatic genome analysis experience. computer science or bioinformatics, including bacterial population genomics and/or
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shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Continuous working with materials requiring personal
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learning and benthic systems. This position offers an opportunity to contribute to cutting-edge research, particularly advancing the use of remote sensing datasets and machine learning for constructing
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related to the project’s objectives. • Process and analyze the collected data by implementing machine learning algorithms and artificial intelligence. • Develop a web-based geospatial interface
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Science, Artificial Intelligence, or a related discipline. You will have experience in BIM and digital construction, digital twins, AI and machine learning, cloud computing, IoT integration, or data
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modelling of electrochemical systems, together with experience in machine learning and data-driven modelling. Research Associate: Hold a PhD in Aerospace Engineering, Chemistry, or a related discipline, or
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. • Expertise in metabolomics with mass spectrometry is desired. • Strong general computer skills, experience with databases and scientific applications, and ability to quickly learn and master various computer
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or peer-reviewed publications. - Previous participation in clinical, translational, or federally funded research. - Familiarity with artificial intelligence or machine-learning applications in medical