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clinical neurology, neuroimaging, and computational modeling. Postdoc Mission: Lead the project efforts in close interaction with on-site neurologists experienced in ALS, experts in Clinical and
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demonstrable background in machine learning including published work. Must have demonstrable experience in building AI models for directed evolution of proteins and protein function prediction and optimization
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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transitions and universality for spectral statistics of random matrices and their applications in high-dimensional statistics, machine learning and probability theory. The Department of Mathematics at KTH
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| Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.03.2032 Reference no.: 5115 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique
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mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time-lapse data Proven programming expertise in
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Signal Processing and Image Analysis group (DSB), Section for Machine Learning, at IFI. DSB has seven full-time and five adjunct positions and carries out research across image analysis and machine
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deadline Experience with urban acoustic monitoring or transportation noise assessment Programming skills in Python Knowledge of machine learning techniques applied to acoustic or environmental data
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machine learning are encouraged to apply. The postdoc will also play a leading role in co-mentoring graduate and undergraduate students, assist in organizing seminars and activities related to RTG
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outputs, and other scholarly measures of impact. Strong demonstrable background in machine learning including published work. Must have demonstrable experience in building AI models for directed evolution