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large-scale genomic, phenotypic, environmental, and field trial datasets, you will benchmark AI and quantitative genetics methods, develop multimodal and hybrid modelling frameworks, and investigate
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experimental cycle from real-time X-ray measurements to post-experiment reconstruction: Develop learning-enabled algorithms for 3D reconstruction of noisy and heterogeneous synchrotron datasets. Implement
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quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational methods to study multiscale
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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and human-based leadership. As organizations increasingly blend algorithmic and human decision-making, fundamental questions arise about how leadership operates, adapts, and creates value in this new
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, gender identity or expression, disability status, liability for military service, protected veteran status, affectional or sexual orientation, atypical cellular or blood trait, genetic information
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Lab’s recent studies on gene regulation, stem cell biology, genome organization, and tissue regeneration have been published in leading journals, including Molecular Cell 2022, Nature Genetics 2023
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you This position provides an excellent opportunity for ambitious researchers interested in applying experimental genetic methods to understand the evolutionary drivers of antibiotic resistance as part
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constraints. The postdoc will work at the interface of reinforcement learning and computational epidemiology, focusing on the development of new reinforcement learning algorithms. The project will consider
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-of-the-art computational methods to investigate the genetic mechanisms underlying neurodevelopment and neurological disorders by integrating single-cell genomic and multi-omic datasets. You will work as part