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for future career development in both academia and tech. Profile Required: PhD in ML, computational neuroscience, physics, engineering, or related field Strong experience in machine learning (PyTorch
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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental
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of biological and statistical physics. Candidates for the position must have a PhD in physics or a related discipline, preferably with expertise in stochastic processes, nonlinear dynamics, and control theory
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surveillance and preparedness planning using multiple modeling approaches. The successful candidate will develop and implement statistical and machine-learning models, integrate multi-source ecological datasets
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strong publication record (first-author papers in high-impact journals preferred). Demonstrated expertise in at least two of the following areas: AI/machine learning for biological modeling (e.g., virtual
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position in machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in concert with collaborators working on diverse scientific and security problems
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, integrate device engineering with clinical workflows, and apply artificial intelligence and machine learning for automated image and signal analysis, tissue classification, and real-time diagnostics
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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] Position Title: Position Type: Postdoctoral Position Location: Lemont, Illinois 60439, United States of America [map ] Subject Area: High Energy Physics / Machine Learning Appl Deadline: none (posted 2025
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related field. Strong knowledge of machine learning. Strong publication record in a relevant field. Excellent analytical and problem-solving skills. Interest in collaborative research with both academia and