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activities. Your Profile: Master and PhD degree in astronomy, physics, computer science or equivalent fields of study. Proven experience in N-body simulations and the comparison of simulation and observation
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algorithm development and application. Familiarity with common scientific programming languages such as C++. Experience in parallel programming with one or more common parallel programming models, like MPI
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cutting-edge laboratory automation in a highly collaborative research environment. About you You will have a PhD (or equivalent) in a relevant area or field related to this project (Computer Science
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scientific results in peer-reviewed journals or conferences. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related discipline completed within the last five
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developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation of results. Deliver ORNL’s mission by aligning
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techniques for the generation and exploration of complex, large-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable
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dynamics simulations using parallel computers or GPU computers. We correlate the obtained results with experimental data on polymeric functional materials to elucidate their dynamic behavior and clarify
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mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Basic Qualifications: PhD in a computational discipline such as Data
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NIH funded laboratory with interest in mechanisms of wound healing, specifically keloid formation. Candidates must have PhD, MD/PhD, or MD or equivalent and must be highly motivated. The successful
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-renowned research institute and work closely with PhD students, PostDocs, software engineers and faculty members on developing cutting-edge AI ready data management. We’re working on extending and