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modelling methods to design resistance-proof antibiotics. You will join an interdisciplinary team, integrating machine learning, medicinal chemistry and microbiology. You will work with Asst. Prof. Eli N
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We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025 BRIDGES project GenePPS, which investigates how machine learning can enable prediction of gene perturbation
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projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
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research, machine learning or artificial intelligence (e.g., large language models, EHR foundation models), causal inference (e.g., target trial emulation), and child health research. The research program
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analytical and interpretability frameworks to investigate the internal representations and decision-making processes of machine learning models. This includes developing and applying techniques such as feature
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demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model
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: Applied mathematics; Machine Learning; Mathematical Modelling Appl Deadline: 2026/03/24 10:59 PM UnitedKingdomTime (posted 2026/03/18 04:00 AM UnitedKingdomTime, listed until 2026/04/01 04:59 AM
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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materials modeling and mechanics, including molecular simulations, multiscale modeling, and/or machine‑learning‑based materials design Demonstrated publication record in peer‑reviewed journals relevant
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hydrological modelling, time-series analysis, and environmental data analysis. • Demonstrated experience in artificial intelligence, including machine learning and deep learning, applied to hydrological