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existing methods to address such risks, and on how to achieve a better use and exchange of existing protocols and data. The project includes the use of Digital Twins to simulate cascading disaster effects
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edge applications. Tasks and responsibilities: Develop new deep learning, computer vision and multimodal learning methods for pre-training and fine-tuning perceptual foundation models. Actively
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the past 2 years [4]. The current industrial standard photovoltaic (PV) module design with difficulty in recycling has generated worldwide concerns regarding an estimated stream of 212 million tons of end
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18 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electrical engineering Physics
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of the proposed methods. Identifying the critical assumptions needed to draw inferences from empirical results. Writing computer code to analyse experimental or secondary data according the best practices and tools
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understandable explanations from machine learning models. We will achieve this together by creating the first mathematical framework for explainable AI and developing new explanation methods. This will involve
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methods. This will involve using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as well as programming to test out
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has been studying any of these topics: statistical physics, computer simulation methods, and polymer physics. Proficiency in the C++ and/or Python programming language is an advantage. Good knowledge
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Strategy. The ability to upgrade methane into higher-value products, particularly through plasma-assisted or catalytic methods, is a game-changer for the chemical industries, enabling a dual focus on
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methods, is a game-changer for the chemical industries, enabling a dual focus on reducing greenhouse gas emissions and creating economically valuable outputs. This PhD position is part of PRIME LEAP, a