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funding; teach courses at the graduate and undergraduate level; mentor students and postdocs in their area of research; and participate in service to the department, university, and discipline
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marketability in these disciplines, gain access to top scientists and state-of-the-art equipment, and gain insight into research and career opportunities. You will have the opportunity to collaborate and learn
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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in
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recently funded centre of excellence (Integreat). Integreat collects scientists from statistics and computer science and offers a flourishing machine learning community, including many PhDs and PostDocs
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philosophers, including one other PhD student (statistics) and two postdocs (spatial forest ecology and philosophy/social science). The candidate is expected to contribute toward developing wholistic adaptive
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experience in scientific computing and software development; familiarity with C++ and Linux environments is an advantage Strong background in deep learning for image analysis / computer vision, ideally
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Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. For more information about AMBER, visit: https
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in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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for postdocs. UNLV currently employs postdoctoral scholars across a wide range of disciplines. Learn more about UNLV's postdoctoral scholars. MINIMUM QUALIFICATIONS This position requires a PhD in Chemistry