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testing data Development of machine learning models for battery health assessment and remaining useful life prediction Job Requirements: PhD degree in Electrical Engineering or related subjects. Expert
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computer programming. Learning to approach novel analytical problems with effective and appropriate solutions. Preparing briefings, technical reports, and manuscripts for publication in professional journals
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environments) remains an open frontier. The new MIT Multi-agent AI Postdoctoral Fellowship Program at Schwarzman College of Computing (MIT MAPS) brings together cutting-edge methods in machine learning
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-C05-i08 of the Recovery and Resilience Program, through the Foundation for Science and Technology - FCT, under the following conditions: Scientific Area: Computer Engineering, Biomedical Engineering
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skills
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implementing bioinformatics pipelines from raw data, applying a range of advanced statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing
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. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches, into simulation design. Conduct
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equipment, computer resources, and yearly research support. Appointments are for one year with the possibility of renewal pending satisfactory performance and continued funding. Candidates are encouraged
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protein coding genetic association data with functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits This position is
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, computational social science, and/or machine learning applications. Acquisition, processing, and analysis of remote sensing imagery. Proficiency with GIS methods, applications, and visualization. Prior experience