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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
is designed for candidates who have completed their PhD within the last two years and have experience as postdocs or industry researchers. This position offers a 12-month term with potential
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Job Description Postdoctoral Associate: Required Qualifications: (as evidenced by an attached resume) * PhD (or foreign equivalent) in Computer Science or a closely related discipline in hand by
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outcomes. The individual will be expected to develop stimulation strategies and testing algorithms, write code, and develop software. They will do extensive validation and testing, under the supervision
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limited to artificial intelligence, computing theory (algorithms, complexity), data science, statistics, discrete mathematics (graph theory, combinatorics), game theory, machine learning, optimization
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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computers or atomic-physics platforms, and quantum algorithms for quantum many-body physics. A PhD in Physics is required. The ideal candidate will have numerical simulation skills with exact diagonalization
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machine learning, modeling algorithms, and/or mapping applications. Applicants must have a PhD in ecology, wildlife sciences or geospatial modeling. Additional Information: Salary Information: Commensurate
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for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section
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machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part