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., Python). * Record of managing and analyzing large-scale genomics or population genetics datasets. * Demonstrated ability and willingness to work both independently and collaboratively. * Ability and
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AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and
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collaborations to implement cosmological analyses derived from the observation of Type Ia Supernovae. This work, carried out within the framework of the ANR SCINF project, aims to develop inference methods based
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development and deployment via deep learning approaches (SE3D)” which is a collaboration between Head of Center and Professor Martin Bøgsted, Center for Clinical Data Science, Aalborg University, Professor
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have the opportunity to collaborate on cutting-edge technologies like quantum simulators, Bose-Einstein Condensates, and quantum information processing. The Chinese University of Hong Kong, Shenzhen is
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applicant will be highly motivated, self-starting, curious, and collaborative. A strong mathematical or computational background and/or programming skill sets will be highly valued. Medical or clinical
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machine learning approaches to investigate the mechanisms underlying GC-biased gene conversion and understand how meiotic recombination shapes human genetic variation and genome evolution. Working closely
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collaboratively. ● Ability and willingness to work in both laboratory and field environments. ● Excellent written and oral English communication skills. Preferred Qualifications: ● Strong background in
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learning, and federated learning. The Postdoctoral Researcher will be primarily based at NYU Abu Dhabi. The researcher will report directly to Dr. Farah Shamout and work in close collaboration with other
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. The work combines physics-based thermal design and process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the final design