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7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research
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research tasks, mentoring junior researchers, and coordinating multi-stage projects. Fluency in Python and modern deep learning frameworks (PyTorch/TensorFlow). Strong analytical, communication, and academic
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highlights, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) You can learn more about the recruitment process here
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow). Experience with eye-tracking data collection or analysis. Familiarity with deep learning frameworks (PyTorch
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Sciences Startdate: 05.05.2026 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 25.08.2026 Reference no.: 5082 Explore and teach at the University of Vienna
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fellowships and NSF SBE postdoctoral awards. We especially welcome applicants with theoretical interest in child language development, strong computational and analytical skills (deep learning frameworks), and
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
/m/x) in Deep Learning and Digital Pathology 102827 Full time 39 hrs./week Neuherberg near Munich Partial Home Office possible At Helmholtz Munich, we develop groundbreaking solutions for a healthier
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of Science and Freie Universität Berlin, Humboldt-Universität zu Berlin, and Technische Universität Berlin. The IMPRS-KIR traces the deep entanglements of knowledge and its resources from a long-term and
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
deep learning (x/f/d/m) Background With the project Deepcloud, we will leverage the machine-learning revolution to understand clouds and their role in the climate system. We aim to train a deep learning