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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
stimulating scientific and industrial environment of the highest level, with access to a national network of leading research institutions and industry partners, regular interactions with the broader EDT
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The exponential growth of computing capabilities has transformed nearly every aspect of modern society. Continuous advances in classical computer hardware architecture and semiconductor technology
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experience levels. Apply a strong understanding of enterprise cybersecurity and technology security challenges. Utilize knowledge of computer network defense tools and processes, including leading commercial
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10 Jul 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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transportation system which include compression and liquefaction. The impurities will pose a safety and lifetime estimation risk to the system as they are very corrosive. There is a need to expand the knowledge
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a large network of researchers at Danish and international universities. Main supervisor is Associate Professor Prajakt Pande. About your responsibilities as a research assistant at CED Your primary
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computer simulations Working in close collaboration with theoretical physicists to test models and develop new insights Your Profile Bachelor's degree in physics Master’s degree/diploma in condensed matter
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models, parameter estimation and model validation). Documented knowledge and experience in data analysis and scientific computing (such as proficiency in Python/R/MATLAB, data visualization, machine
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languages, including Python, C++, or Java, focusing on algorithms and data structures applied explicitly in computer vision projects Knowledge of machine learning and deep learning frameworks, including
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experiments and policy-capturing methods may be used to compare interviewer judgements with evidence-based outcome measures. The project will also explore machine-learning, multimodal data analysis, computer