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, Mathematics, Physics, or a closely related field. Proficiency in machine learning libraries (e.g, scikit-learn, PyTorch, and transformers) and data analysis tools (e.g., pandas, NumPy, and CuPy). Hands
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Resource Management conducts education and research in the areas of forest planning, forest remote sensing, forest inventory and sampling, forest mathematical statistics and landscape studies. The department
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under special circumstances, such as statutory leave. The research tasks require a solid mathematical background with proven advanced experimental capabilities and excellent programming skills (e.g. C
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Mathematics, Computer Science and Artificial Intelligence. The environment fosters truly interdisciplinary research with a great track record of national and international collaboration transferring knowledge
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defended their dissertation prior to the start date) with a background in water resources (not necessarily from Civil Engineering). A background in applied mathematics, field methodologies in unconsolidated
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neuroscience or equivalent field. Sufficient mathematical, biological, or equivalent expertise to perform research. Preferred Qualifications: Experience in behavioral neuroscience, good writing and speaking
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RIKEN, Center for Interdisciplinary Theoretical and Mathematical Sciences Position ID: RIKEN -iTHEMS -RQW24328 [#29715] Position Title: Position Location: Wako, Saitama 351-0198, Japan [map
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 19-Aug-25 Location: Boston, Massachusetts Type: Full-time Categories: Academic/Faculty Physical Sciences Internal Number: 6480939 Postdoctoral Research Associate About the Opportunity The Postdoc will be working on...
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About us The Department of Chemistry is a dynamic and collaborative environment within the Faculty of Natural, Mathematical and Engineering Sciences, dedicated to cutting-edge research and academic
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theoretical ecology, geosciences, applied mathematics, environmental physics, or a related field. Research experience in numerical modelling, preferably with knowledge of either eco-evolutionary models and/or