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is led by Professor Mauro Giacca and comprises over 65 clinical and non-clinical academic groups, hosting 400 personnel and 110 PhD students. Our community of world-renowned researchers and educators
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for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets
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emerging spectrum (FR3, MMW, sub-THz/THz) Extreme massive MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless
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/Python coding, next-generation sequencing data interpretation, large-scale data integration, and machine learning. Science: strengthen the ability to formulate hypotheses, design aims to test the
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-$60,000 Type of Position Student Position Time Status Full-Time Required Education PhD Required Related Experience N/A Required License/Registration/Certification N/A Physical Requirements Check all
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computing, computer architecture, programming models and high performance computing. These are your qualifications: Must-haves: Completed doctoral/PhD studies in Computer Science or a closely related field
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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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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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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