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Field
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, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine learning) or a directly related field at the time of appointment is required. The successful applicant
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materials property predictions. A deep understanding of materials properties and close connections in academia and industry enable the group to explore exciting research avenues. For more information about
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Control engineering (experience with nonlinear systems is a plus) Machine learning and deep learning in context of physical systems Programming skills are required, with Python experience preferred. A good
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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
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are comfortable navigating complex HPC environments and wrangling large datasets. You have experience with modelling through state-of-the-art machine and deep-learning methods and with hands
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data from both tissue and single cells, for improved understanding of Alzheimer progression. Experience in brain disorders, machine learning and deep learning will be a plus. Interested candidates should
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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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associate will also provide leadership in coordinating different projects and advising more junior lab members. The current and prior work of the lab include deep learning algorithms for detection
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artificial intelligence techniques: deep learning or swarm intelligence is a plus but is not required. The annual base salary range for this position is $85,000 - $100,000. When extending an offer
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bioinformatics methods have made significant strides, AI approaches - particularly deep learning - are revealing patterns and relationships in biological data that were previously inaccessible. As a postdoctoral