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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
of microscopy, multiplexed immunofluorescence, spatial/protein imaging, or image-derived single-cell phenotypes. Machine learning, latent variable modeling, variational autoencoders, optimal transport, graph
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Difallah in the Division of Science, New York University Abu Dhabi, seeks a Post-Doctoral Associate or a Associate Research Scientist to join a lab focused on applied machine learning. The successful
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associate will be conducting research on topics in machine learning and computational materials science.. In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is
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team, as well as the willingness to learn new methods and techniques and to collaborate with others as the projects evolve. Pay Range: $63,480.00 - $71,000.00. Salary will be commensurate with
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and/or case-crossover analyses, and have a promising publication record. Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization
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XRD, and the analysis of complex materials datasets · proficiency in quantitative analysis, computational methods and programming, with experience in AI, machine learning or data-driven materials
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the computational task: first-principles active-site descriptor models, high-throughput screening with machine-learned interatomic potentials, and a dedicated catalysis database. This position is ideal for a
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Physics Informed Machine Learning method which exploits the advantages of physics-based and data-driven models, while mitigating the disadvantages. This research will contain experimental and modelling
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
students, and collaborate with AI faculty in vision, robotics, and machine learning across the department. Minimum Education and Experience Requirements Applicants should have, or expect to receive before