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Field
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develop novel learning-based control and policy optimization techniques. We're looking for a skilled machine learning (ML) engineer to develop cutting-edge AI algorithms for digital twin applications in
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. Your task in detail: Design a data pipeline to extract and preprocess activity-relevant features from monitored building power consumption data Develop a classification algorithm (e.g., based on Gaussian
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of Computer Science seeks to employ two Research Associates to work within a research group, reporting to Associate Prof. Mahsa Shirmohammadi and Vincent Cheval. The postholders will carry out research on the ERC
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) Established Researcher (R3) Application Deadline 31 Jul 2026 - 12:00 (UTC) Country Italy Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme
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learning, edge computing, development of novel AI algorithms for agricultural applications, embodied AI, simulation to reality transfer, and systems engineering incorporating big data and artificial
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-guided design-build-test-learn workflows, and open algorithms, benchmarks and reproducible research. This is an exciting opportunity to help shape a frontier AI for Biology programme, publish high-impact
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clear updates on program status to Fleet-level personnel at both individual and community meetings Interact and collaborate regularly with the engineering team, principal investigator, sponsors, and other
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project tasks Develop and deliver clear updates on program status to Fleet-level personnel at both individual and community meetings Interact and collaborate regularly with the engineering team, principal
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project tasks Develop and deliver clear updates on program status to Fleet-level personnel at both individual and community meetings Interact and collaborate regularly with the engineering team, principal
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Computer Science, Information Systems or related technology field, or an equivalent combination education and experience. Certifications/Licenses Required Knowledge, Skills, and Abilities Highly motivated candidate