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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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of developing simulators for Post-Von Neumann architectures. The candidate would become a member of the Innovative Computer Architecture group and become part of the CogniGron research centre as well as the NL
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technologies and manufacture processes with emphasis on mechanical and materials engineering. For more information about the APE group please use the following link: www.rug.nl/research/ape. Qualifications
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12 Sep 2025 Job Information Organisation/Company University of Groningen Research Field Physics » Biophysics Researcher Profile First Stage Researcher (R1) Country Netherlands Application Deadline
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25 Sep 2025 Job Information Organisation/Company University of Groningen Research Field History » Medieval history History » Modern history Researcher Profile First Stage Researcher (R1) Country
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, current policies and programs have struggled to achieve their goals. Top-down, market-driven approaches, which rely on financial incentives and standard information dissemination, often fail to engage
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spectroscopy data and AI, to automatically identify textile fabrics with high accuracy in real-world sorting conditions by (1) defining optimal spectral bands, spatial resolution, and acquisition speed; (2
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testing, to achieve sub-second cycle times for robotic systems. 3. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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. Diplomas (BSc and Msc) and transcript of records. Contact information of two academic references. You may apply for this position until 15 October 11:59pm / before 16 October 2025 Dutch local time (CET) by
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of annual leave. We aim at a starting date of 1 November 2025 For more detailed information about working conditions and working for the University of Groningen, please check: www.rug.nl/about-us/work-with-us