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Field
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experiments is strongly required Programming expertise in Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability to model Argonne’s Core
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automation methodologies and software infrastructure for next-generation computing systems, including neuromorphic and emerging hardware platforms. The position involves designing high-performance algorithms
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Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing
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, research, and public service. Job Description Purpose: The Department of Electrical and Computer Engineering and AggieFab Nanofabrication Facility at Texas A&M University seeks a Postdoctoral Researcher to
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The Multiphysics Computations Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee for performing high-fidelity scale-resolving computational fluid dynamics (CFD
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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 4 hours ago
This postdoctoral researcher will play a key role in a theoretical and computational research program focused on axion physics and cosmic microwave background (CMB) cosmology. This research program is led by
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Computational modeling of metal alloys using an Integrated Computational Materials Engineering (ICME) approach. Responsibilities: 60% Perform research on the microstructural evolution of metal alloys during
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. Experience working with a high-performance computing (HPC) environment. Familiarity with machine learning and advanced statistics. Experience with analysis of time series data from intracranial EEG (iEEG
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-performance computing systems (,e.g., SLURM) Familiarity with population genomics, GWAS, or related approaches Experience with large biological datasets Proven ability to communicate scientific information