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-derived motor neurons and Drosophila models. Now, we need a curious and driven PhD candidate to help us analyze these samples using spatial multi-omics. This is a joint project between Prof. Albena
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collaborations between the Department of Biosciences, the Natural History Museum, the Department of Mathematics, and the Department of Philosophy. To respond effectively to the accelerating decline in biodiversity
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Develop solutions to integrate large foundation models
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 1 month ago
system. Climate models are important tools for improving our understanding and prediction of atmosphere, ocean, and climate behavior. We seek candidates with an interest in advancement of radiative
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(USMB). Its scientific activities span cosmology and astroparticle physics, particle physics, and mathematical physics. The Astroparticle and Cosmology group (https://astrocosmolapth.com ) conducts
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scoping to deployment and monitoring of production-grade models—with a focus on both Generative AI and Deep Learning. The ideal candidate holds a Ph.D. in Deep Learning or Generative AI and brings a strong
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analytical methods and computational models that support collaboration quality between students and LLMs in educational settings. The research combines approaches from learning analytics, computational
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-time postdoctoral grant in Probability and Statistical Physics - CY Cergy Paris University Mathematical modelling of complex systems often involves combining deterministic structures with probabilistic
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science and economics and finance. Leveraging its ‘4-in-1’ model of education and residential college system, UM provides all-round undergraduate education, nurturing talent to support social and economic
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Marie-Skłodowska-Curie Action (MSCA) grant on WindConnect project. The project The WindConnect (wind farm control and integration in sector-coupled power systems https://cordis.europa.eu/project/id