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Field
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be studied rigorously. Applicants may have a background in natural language processing, computational linguistics, computer science, machine learning, artificial intelligence, data science, digital
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. A strong background in energy-system modelling, mathematical optimization, machine learning, reinforcement learning, or data-driven decision-making is appreciated. Experience with programming and
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Laboratory and field-based structural testing and data acquisition Direct and indirect sensing methods for bridges, including remote sensing techniques Machine learning and artificial intelligence for
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HCI, machine learning, biosensing, and accessibility. You will design and evaluate trustworthy, interpretable XR experiences in a joint DTU-KTH project with co-supervision and extended research stays
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demonstrated its potential to support people with limited arm and shoulder function. Your task will be to explore and develop an AI-enhanced Human-Machine Interface (HMI) that enables a more intuitive and
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-manual dexterous setup to reliably solve complex assembly tasks. The following works conducted at the lab will serve as a basis for the internship: https://cea-list.github.io/cotograspweb/ https://cea
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resolution and remission” Employer Charité - Universitätsmedizin Berlin Location Berlin (DE) Salary salary grade W2 under the BBesG ÜfBE Closing date 23 Oct 2026 Website https://www.charite.de/en/ View
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Intelligence and Machine Learning development, Proficiency in written and oral communication in English. Place of employment: Karlskrona. Employment level: 100%. Commencement: Early Fall 2026, exact
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, writing, speaking). • Show ability to work independently as well as in a team. • Good knowledge in AI, machine learning, data science and mathematics. • Good knowledge in one or more of the following
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advising is desired. Special Instructions Please submit the following materials through the ARIeS portal ( https://academicpositions.harvard.edu ). Review will begin on November 1, 2026; applications