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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Establish and validate a regional coupled ocean modeling framework at very
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, numerical methods, and Earth system modeling to develop and evaluate a coupled xylem–phloem transport framework that translates multiscale physics into next-generation vegetation model schemes. Key
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 23 hours ago
opportunities to model and predict socio-demographic and economic indicators over the life course. This project would combine powerful predictive tools with approaches from causal inference to advance our
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methodologies. The focus is on across-organ imaging, ranging from non-human primate (NHP) models to human applications. You will contribute to the development and application of state-of-the-art MRI techniques
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prediction approach for pennycress and winter camelina improvement. Post-Doctoral Associates conduct research and/or services that provide further development of career skills or allow them opportunities
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prediction of gene perturbation effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural
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and sequence-based mechanisms of gene regulation. Current projects focus on deciphering the regulatory landscape of the human genome by integrating AI-driven enhancer modeling with GWAS data and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
to the weather prediction and climate projections. This is mainly due to our lack of understanding of cloud/snow ice microphysics and over-simplified representation in models. On a broader sense, although weather
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discrete black box combinatorial optimization problems (https://arxiv.org/abs/2510.01824 ). In this work, we parameterize a multivariate autoregressive generative model for generating solutions. By sampling