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of machine learning researchers, engineers, and domain scientists. This collaborative environment offers a unique opportunity to work on cutting edge AI models, with a focus on generalization and
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of the distinguished Association of American Universities. Connections working at New York University More Jobs from This Employer https://main.hercjobs.org/jobs/22209243/postdoctoral-associate-x28-chen-lab-x29 Return
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
methodology, machine learning, and biomedical data science. Our research develops rigorous and interpretable methods for high-dimensional biomedical data, with applications spanning cancer genomics
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, Applied Mathematics, or Computational Physics/Chemistry with a strong ML focus. Technical: Deep understanding of Deep Learning (Transformers, GNNs, Auto-encoders). Programming: Proficiency in Python and
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science, or a related field; experience with using and building machine learning models, developing and validating computational analysis workflows, and developing circuit models is preferred; excellent
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genes, neural circuits, and behavior. For more information about our work, visit https://www.bayer-lab.org/research This position is for a post-PhD trainee. The Postdoctoral Associate will develop and
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar
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the groups of Dr Joe Forth, Dr Anthony Bradley, and Project Lead Professor Steve Rannard, applying your expertise in machine learning, cheminformatics, and soft materials to accelerate LAT design and
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-physical systems security, protection of critical infrastructure, and adversarial machine learning. The position will involve collaborating with faculty and graduate students on interdisciplinary research
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. Job Description: Two postdoctoral researcher positions are available in the laboratory of Dr. Sarah Kim (https://pharmacy.ufl.edu/profile/kim-sarah/) to apply modeling and simulation approaches