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programming skills (C++ or Python) and experience with numerical modeling (for instance, Finite Element Analysis or Computational Fluid Dynamics); A strong interest in—and willingness to learn and perform
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 4 days ago
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Starting date
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The Chicago School of Professional Psychology | Washington, District of Columbia | United States | about 21 hours ago
on quantitative and qualitative research methodology. The Research Methods course focuses on the appropriate methodologies for program and intervention outcome analysis, linkage research, and model testing
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Section, Nuclear Energy and Fuel Cycle Division at ORNL is seeking candidates to apply for the computational nuclear engineer role. This role is responsible for the development and implementation of methods
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for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics-aware learning methods with domain decomposition techniques, enabling parallel training and
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you advanced skills and experience conducting statistical analyses within health, biomedical or related research fields demonstrated understanding of quantitative methods, including regression modelling
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RAP opportunity at National Institute of Standards and Technology NIST Advanced Methods for Measuring Microbial Viability Location Material Measurement Laboratory, Biosystems and Biomaterials
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, methods-led research career at the intersection of advanced analytics and applied mental health research, within a highly collaborative and multidisciplinary environment. About the role The PDRA will be
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 21 hours ago
. Preferred Education, Knowledge, Skills and Experience Experience in High Performance Computing related technologies such as schedulers, parallel computing, storage systems, or scientific applications
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or more of the following areas: theory for spatial discretisations of PDEs, analysis and design of domain decomposition methods, numerical analysis for stochastic PDEs, numerical analysis for multiphysics