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: Experience in physical system modelling including finite element modelling Experience working with large codebases in open source software environments Proficient user of HPC environments including MPI
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operations, and additive manufacturing. Through multiple external funded projects, UTRGV IAM builds strong research, education and exposure programs for defense materials and manufacturing, energy
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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trainee position to pursue research as a vital component of their educational mission and professional career development. Works under minimal supervision with some latitude in the use of initiative and
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publications; disseminate study results and research findings in journals and conferences. Perform advanced computational modeling using finite difference and discrete element modeling programs. Perform advanced
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to deliver defibrillators. Collecting and analysing qualitative and/or quantitative data across multiple work packages. Working closely with 999 call handlers, drone operators, public contributors, and
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for Multi-Agent Decision-Making, https://oceanerc.com ). This timely project will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making
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. - Develop new nonlinear finite element models to address key data gaps in steel component behavior. - Translate findings into technical guidance that informs seismic design for damage control, post
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
therapeutics. Position Overview: We are seeking multiple highly motivated Postdoctoral Research Fellow with expertise in systems pharmacology, machine learning, and/or data science to join our interdisciplinary