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with the ARIA Safeguarded AI programme project “Data-Parallel Proof Checking for Monoidal Theories”, led by Professor Fabio Zanasi within the Programming Principles, Logic and Verification (PPLV
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help unlock the data needed for the energy transition? In the NWO-funded SHARE project, you will develop AI models that generate realistic, privacy-preserving synthetic energy data for grid planning
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central focus is the creation of AI-driven medical digital twins by integrating large-scale genomics, multi-omics, and longitudinal health data. We are an interdisciplinary and collaborative team
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for data-driven models and high-dimensional data. The position is full-time for two years, starting on 12th January 2026, or as agreed upon. The Department of Computing Science at Umeå University is an
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We are offering a three-year PhD fellowship in pharmaceutical data science focusing on database design for amorphous pharmaceuticals commencing 15 November 2026 or as soon as possible thereafter
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PhD student in generative modeling for data-efficient machine learning Norrkoping Reference number LiU-2026-02831 We are now looking for a PhD student in machine learning with a focus on generative
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compression and its co-optimization with memory technology characteristics and constraints. You will work within CEA-Leti and CEA-List institutes, benefiting from a forefront ecosystem for AI model
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Vacancies Doctoral Candidate Spatial statistics for integrating IoT field sensor data and remote sensing data for nature-inclusive solutions in tree crop diseases To vacancy overview Apply now ITC
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Bionic neural engine. Compared to cloud-based machine learning services, on-device ML is privacy-friendly, of low latency, and can work offline. User data will remain at the mobile device for ML
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Bionic neural engine. Compared to cloud-based machine learning services, on-device ML is privacy-friendly, of low latency, and can work offline. User data will remain at the mobile device for ML