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anthropology, sociology). You are eager to engage with fundamental questions about language and technology. You bring solid technical skills and deep, critical understanding that you wield for thoughtful
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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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analysis of PDEs (with deterministic and/or stochastic methods), Gaussian Random Fields, mathematical foundations of deep learning, functional analysis and measure theory. You can find more information about
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on the development, ecology, evolution, and physiology of marine organisms worldwide from the intertidal zone to the deep sea. Position Summary The Oregon Institute of Marine Biology seeks qualified applicants for its
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). Team player and great collaborator Strong interest in interdisciplinary work at the interface between dementia/ neurodegeneration, modeling, and machine learningPrior experience in deep learning, or/and
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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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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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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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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). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored