84 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" uni jobs at Chalmers University of Technology
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deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an interest in their application to embodied systems. What
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an innovative spirit, in close collaboration with wider society. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com
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data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods
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background. However, for this project you must also be open to learn to include social science perspectives on the energy transition by means of cooperation with other research groups. Who we are looking
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conducting research "in the wild" (e.g., field deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an
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technology, and to build a Swedish quantum computer). Within AQP, the group of Anton Frisk Kockum has the overarching goal of providing humanity the tools to understand and use large quantum systems. Working
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initiative started in 2018 with the purpose of advancing Swedish academia and industry to the forefront of quantum technology, and to build a Swedish quantum computer). For the research on quantum optics with
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at the division of Computer and Network Systems , where we design secure, dependable and high-performance computer and communication systems that meet the demands of an increasingly digital and interconnected world
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methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods. Special
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complex behavior under demanding operating conditions presents a significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while