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Postdoc Impact of Computational Infrastructures on Public Institutions and Administration of Justice
2 Sep 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Informatics Political sciences » Public policy Sociology » Social shaping
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for computing performance guarantees of autonomous AI agents under uncertainty, which will be integrated to various degrees into a use-case with self-driving shuttles. Based on your experience and interests, you
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-based, probabilistic, and in-memory computing, are based on a wide variety of physical processes, materials, architectures, and algorithms. For effective implementation, these aspects need to be mapped
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Challenge: How do we enable continuous robot learning in shared
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Application Deadline 21 Sep 2025 - 21:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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analysis and dose verification (depending on your experience). What you will do As a postdoctoral researcher, you will: Independently carry out experimental and computational research within
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Dutch and English. Affinity or experience with innovation projects involving partners from practice. Willingness or experience in programming heuristics and algorithms. Motivation to produce academically
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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researcher with expertise in the area of spiking neural networks and an interest in (applications of) probabilistic computing. The postdoc candidate will participate in the NWO NWA project "Acting under
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data