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Responsibilities We are looking for a highly motivated Postdoc in the areas of Probabilistic Machine Learning and Neuro-Symbolic AI to contribute to the Cluster of Excellence “Bilateral AI (BilAI),” funded by
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soon as possible Job Reference Number: 36400-2026-001900 One of the EU’s leading machine learning hubs. A team with continuous high-impact publications (e.g., Nature, Science formats. Unique
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programming and instrument control using Matlab, Python, Labview etc Machine / deep learning expertise Strong analytical skills and ability to work in a multidisciplinary team Excellent communication and
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.; formal validation/verification of protocols and implementations; biometric authentication and machine learning for usable security; or OT (operational technology) security Communication and organizational
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Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 15 May 2026 - 23:59 (Europe/Vienna) Country Austria Type of Contract Temporary Job Status Negotiable Is the job
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the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 3 months ago
-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Open Postdoc
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, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7
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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | about 1 month ago
, Approximation Theory, Machine Learning, Inverse Problems and Regularization Theory. Proficiency in programming with a strong preference for Python and deep learning frameworks such as PyTorch is highly desirable
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the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists