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in one or more of the following areas: computational biology/bioinformatics, biomedical informatics, deep learning/machine learning, data mining, biostatistics, or a closely related area. Proficiency
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groups to study cancer biology using deep clinicogenomics data and cutting edge NGS diagnostics. The Opportunity: Opportunity to drive scientific, analytic, and technical innovation in a community of
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foundations of deep learning, functional analysis and measure theory. You can find more information about our research area and our team on the website: http://www.olgamula.com. As a team, we understand the
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on the training strategies. In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have
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States of America [map ] Appl Deadline: (posted 2025/01/10, listed until 2025/07/10) Position Description: Position Description Multiphysics, Machine Learning, and Uncertainty Quantification Postdoctoral Positions Los
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50 Faculty of Life Sciences Startdate: 01.08.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.07.2029 Reference no.: 4160 Explore and teach
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, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing ● Emerging AI/ML models and hardware
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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following areas: 1) statistical genetics/genomics/omics, or 2) deep learning/AI. Most importantly, we value candidates who demonstrate both the ability and drive to rapidly learn and implement recent advances