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computations relevant to the development of strategic nuclear performance codes for nuclear reactors. This position resides in the Radiation Effects and Microstructural Analysis Group (REMAG) in the Materials in
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), to work on problems at the intersection of biology, medicine, mathematics and computation. The successful candidate will contribute to the development of next-generation learning algorithms to understand
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The Morrow Laboratory at the Albert Einstein College of Medicine in the Bronx, New York city is recruiting postdoctoral fellows with interest in mouse cardiac development. We are seeking applicants
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developing novel methods and algorithms for applications in the Engineering Design domain; demonstrating a commitment to deliver results; working on research proposals; and working in a team environment. Job
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on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position collaborates with faculty, students, and external partners
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Posting Details Position Information Posting Number PG191517PD Position Number 00111548 Position Type Post Doc FLSA Departmental Information Department ID 120401 - Landscape Architecture Department 120401 - Landscape Architecture Job City & State Raleigh, NC
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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learning algorithms and creating predictive models. This role will contribute to evidence-based processes and procedures for program quality review and assessment of outcomes data as well as develop
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms