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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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of image processing e.g. using machine learning German skills For further questions, contact Dr. lmke Greving (imke.greving@hereon.de). We offer you an exciting and varied job in a research centre with
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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
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apply statistical and machine learning models to identify predictive markers of depression. Design and execute experimental protocols related to self- representation and chronic pain. Prepare manuscripts
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motivated post-doctoral associate with a strong background in control systems and machine learning to join the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subjects of the research are: AI-assisted Bond Issuance, Causal
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for individuals preparing for academic careers in statistics, biostatistics, machine learning, or related fields. The postdoctoral researcher will be supervised by Dr. Razieh Nabi. For inquiries, please contact
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, regression models or machine learning. Applicants from clinical hepatology with experience in the above fields can also be interesting. You will work in an interdisciplinary and international research
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27.10.2025 Application deadline: 30.11.2025 Are you excited about the possibility to explore ethical, philosophical, legal, epistemic or social implications of using machine learning in different