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modelling the coupling of atmospheric and micro-physics moisture dynamics. The work will be carried out in collaboration with and under the supervision of Professor Edriss S. Titi. Duties include mathematical
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-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis
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bending and trafficking. We utilize a blend of mathematical modeling, genome-editing in human stem cells, and fluorescence microscopy. Our projects aim to elucidate the emergent architectures and modes
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; representation from three continents). Our lab’s strength lies in integrating multiple disciplines: Single-cell microfluidics Quantitative (image) analysis Mathematical modelling Microbiology Molecular biology We
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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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Okinawa Institute of Science and Technology, Pure Mathematics Position ID: OIST -PDLS2026 [#26851] Position Title: Position Type: Postdoctoral Position Location: Okinawa, Japan [map ] Subject
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learning or applied mathematics. Required skills and qualities: - Fluency with Python programming for data analysis or machine learning, - Knowledge of statistical or probabilistic modelling techniques
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assigned to the research project "Randomization of Surrogates for the Quantification of Domain Uncertainty Propagation in Cardiovascular Models" as part of the Berlin Mathematics Research Center MATH+. The
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025, and will remain open until excellent fits are found.The