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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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(KCL, London, UK) but will also have the opportunity to travel and work at the Centre for AI and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU
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electronic structure theory (e.g., density functional theory), and machine learning based computational studies of molecular and periodic systems. The postdoc will also work within a multidisciplinary multi
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal
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staff, PhD candidates and Postdoctoral researchers in the Computer Engineering group. Curious to learn more about the project, and perhaps our group? Feel free to browse our webpages: Job requirements For
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(TUE), CWI, IMEC and Delft University of Technology. You will be part of a diverse and passionate research team of academic staff, PhD candidates and Postdoctoral researchers in the Computer Engineering
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strategies. The candidate will join the Machine Intelligence Group for the Betterment of Health and the Environment (MIGHTE) led by Prof. Mauricio Santillana. MINIMUM QUALIFICATIONS PhD in a quantitative field
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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
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Pythonis; and experience with tokamak physics or machine learning techniques. The appointment will be for two years with the possibility of renewal based upon satisfactory job performance. Application
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collisions and maximize efficiency through innovative AI-based movement and maneuver planning. For the first time, innovative machine learning concepts, such as “shadow learning”, are being used. Appropriate