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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and/or Python; best practices in reproducible research Excellent
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applicants who combine strong quantitative skills with a deep interest in the fundamental mechanisms shaping plant communities and their response to climate change. Qualifications: • PhD in Ecology or a
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, deep learning, or statistical modeling. Demonstrated experience working with clinical, digital health, or related biomedical data. Proficiency in Python, R, or other scientific programming languages
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, or a related area. Graduate students near completion of their Ph.D. are welcome and invited to apply. Experience 0+ years of postgraduate experience. Skills Successful candidates should have: · Deep
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processing ● Proven experience in scientific programming in Python and/or C++ ● Deep familiarity with collaborative software engineering practices (Git, testing, code reviews, CI/CD) ● Demonstrated
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/ ) research examines learning and conceptual change in young children with a focus on social learning and social cognition. Research topics include: mechanisms of causal learning, the developmental origins
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position. Group members are involved in the COHERENT experiment at the Spallation Neutron Source at Oak Ridge National Laboratory, the Deep Underground Neutrino Experiment, Super Kamiokande, and T2K
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, United States of America [map ] Subject Areas: Engineering / Computational Science and Engineering , Machine Learning , Quantum Science and Engineering Appl Deadline: (posted 2026/03/05 05:00 AM UnitedKingdomTime, listed
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the global health scenario and domestically for dissemination, and plenty of opportunities for career advancement. •Learn background/research methods of studies for which analysis is conducted with limited