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Dovrolis: PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity. ICML 2025 Job requirements Master’s degree in: Computer Science, Machine Learning
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of machine learning, and/or ecological modelling. Excellent oral and written English language skills. Strong collaborative skills, team spirit and the ability to also work independently. Experience with field
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PixHawk Autopilot, Arduino boards, Raspberry Pi - or equivalent Experience with ROS/ROS2 Experience with programming languages like Matlab, Python, C++ Familiarity with machine learning and/or deep learning
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to the different situations and the benefits or costs that come from the group dynamics. We will moreover compare different types of collective problems (cooperation, coordination…) and investigate if and how global
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industry and academia together to drive pre-competitive, fundamental research in polymers. We welcome applicants with interests in polymer physics, materials processing and characterisation, machine learning
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, machine learning, and photonics. Be part of a multidisciplinary research team spanning science and engineering. Access state-of-the-art laboratories and high-performance computing facilities. Gain
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Science, Machine Learning, Finance, FinTech, Economics, or a related field. Candidates should demonstrate knowledge of Large Language Models, generative AI, and machine learning, with interest in financial
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platforms, e.g. aerial drones, climbing robots, and remotely operated underwater vehicles, for capturing degradation data across turbine blades, towers, foundations, and subsea cables; (2) develop a machine
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily
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for part-time employment. Starting date: 27.03.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date