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, reliability, and consistent behavior. Learning-based controllers can achieve high performance in complex and uncertain environments, yet ensuring predictable operation under distribution shifts, sensor noise
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NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will involve collaboration with
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. The successful candidate will lead the development of next-generation wearable devices specifically designed for spinal cord injury applications. This role involves the end-to-end development of advanced sensor
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their professional network and skill set. We are therefore seeking a researcher who is comfortable working with multiple collaborators and engaging with patient groups and other stakeholders. There will also be
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important pathogens. About you The successful candidate will develop and apply genome analysis pipelines to identify potentiating mutations and/or gene gains on projects across the IOI and PubMLST network
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research with Professors Mario D. Molina, Minsu Park, and Blaine Robbins. We seek candidates with research interests and expertise in social networks, group or organizational dynamics, and computational
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network and is a research-intensive department. We expect academic excellence and offer an inspiring and stimulating working environment, flexible working hours and excellent opportunities for professional
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: Ph.D. in Physics, Computer Science or closely related areas Preferred: Demonstrated strength in one or more of the following. - Quantum many-body numerics: tensor-network methods, variational Monte Carlo
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An international network within the field Excellent collaborative skills Who we are PREDICT is at the forefront of international research to unravel the cause and prognosis of inflammatory bowel diseases (IBD
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Semiconductor Manufacturing and Research Technology Innovation Corridor (NY SMART I-Corridor) Tech Hub initiative, the Center for Supply Chain Analytics leads the Supply Chain Activation Network (SCAN) project