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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer
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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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Michael Bronstein, AITHYRA Scientific Director AI and Honorary Professor of the Technical University of Vienna in collaboration with Ismail Ilkan Ceylan, expert in graph machine learning, invites
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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comes with no teaching obligations BASIC RESPONSIBILITIES AND OBLIGATIONS Conducting research related to the scientific project titled “Calculus of variations in machine learning problems”, in particular
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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research approaches. Working closely with nursing partners and clinical collaborators, our exciting work combines non-invasive imaging technologies, deep learning, computer vision, and clinical workflow
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performs MRI research and development of advanced multiparametric methods for the evaluation of primary and metastatic brain tumors. Recent work incorporates machine learning methods to advance
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to join our team. Our lab focuses on developing and applying innovative statistical machine learning methods, single-cell multi-omics, and systems immunology approaches to investigate immune-mediated