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-cultural. EPFL covers a wide spectrum of science and engineering and offers a fertile sSchool of Basic Sciences include theoretical and experimental biophysics, biological imaging and physics of machine
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motivated the development of Federated Learning (FL) [1,2], a framework for on-device collaborative training of machine learning models. FL algorithms like FedAvg [3] allow clients to train a common global
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Curriculum and other under and post graduate degree programmes that involve the Faculty of Medicine. Further, they will be expected to teach in areas outside their specialisation. The successful candidate will
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experience in programming and working with large-scale data; expertise in machine learning is a strong plus. Ability to work in a highly collaborative and interdisciplinary environment. Experience implementing
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contribution of genetic and non-genetic driving forces for the cells’ evolution and glioma development. Using multi-omics data integration and machine learning, we will investigate cellular behaviors and gene
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geological field-based methods and big data applications and machine learning methods. Research focus will be on feedback processes between erosion, sedimentation, tectonics and climate, and topics could
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NOVA Institute for Medical Systems Biology (NIMSB) announces Four Independent Group Leader positions
for integration of large-scale omics datasets, and application of machine learning and statistical modelling for decipher cell and tissue behaviour, elucidate disease mechanisms, and enable patient stratification
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dedicated to discovering and refining the core mechanisms that will enable machines to learn continuously, make robust decisions in complex environments, and evolve autonomously. Key research directions
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, energy, sustainability, etc.). Besides these research-focused areas, we expect the successful candidate to be able to contribute to our teaching portfolio within e.g. data science, machine learning, IoT
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to contribute to our teaching portfolio within e.g. physical computing, cyber-physical systems, machine learning, sensing and IoT, etc. We additionally expect the successful candidate to have a flair for