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members have been working on statistics learning, granular computing and knowledge discovery, machine learning, deep learning, and specifically interpretable artificial intelligence. Many innovative
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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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and energy distributions at the substrate level, as well as deep knowledge of plasma-surface interactions. - Strong written and oral communication skills; ability to work independently and as part of a
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environment where machine learning meets real-world scientific impact. What You’ll Do: Conduct cutting-edge research at the intersection of AI and science Develop large-scale deep learning models for scientific
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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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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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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 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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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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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