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extracellular matrix biology, biomaterials, hydrogel systems, 3D culture, tissue engineering, or disease-relevant cell–matrix models. About the School The School of Physical and Chemical Sciences (SPCS) at Queen
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experience applying artificial intelligence or machine learning to scientific or engineering problems, including the development, training, validation, or evaluation of machine-learning models. Proficiency in
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engineering faculties worldwide. For more information, visit the Faculty website: https://www.unsw.edu.au/engineering/about-us Skills & Experience: A PhD in Photovoltaic Engineering, Materials Engineering
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 6 days ago
inform representations and encoder adaptations. This activity will provide hands-on experience in making three-dimensional vegetation structure accessible within data-driven geospatial modeling processes
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assigned Requirements A Ph.D. degree in Neuroimaging, Biomedical Engineering, Electrical Engineering, Physics, Computer Science, or other related disciplines, with experience or keen interest in processing
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rigid body dynamics, biomechanics, and neural mechanisms, and applying data-driven methods to learn or identify models from empirical data. Notice of Non-Discrimination and Equal Opportunity
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of Chemical and Biological Engineering Posting Number R260133 Posting Link https://www.ubjobs.buffalo.edu/postings/64055 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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Position Description Department of Biological & Environmental Engineering Postdoctoral Associate The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose-driven science and
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antigens presented by MHC molecules. This curiosity-driven project develops cutting-edge AI technology for 3D TCR–pMHC modeling to improve neoantigen identification, TCR specificity prediction, and TCR