17 software-engineering-model-driven-engineering-phd-position Fellowship research jobs
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dissemination of results. Required selection criteria A completed PhD in Computer Science, Cybersecurity, Artificial Intelligence, Software Engineering, or a closely related field. Strong background in using AI
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systems, thermal energy storage, data-driven building control systems and other novel solutions for the urban built environment sector. This position is to recruit a member of the research team to work on a
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to develop cutting-edge theories, methods and technology, for efficient, effective and responsible exploitation of data-driven AI in industrial solutions. Currently the center concentrates their activities
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organizational skills and interest for data-driven research Positive attitude and the ability to handle hectic periods Employment in the position is based on a comprehensive assessment of all qualification
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, an environment, and a culture that just aren’t found together anywhere else. This is the right place for you if you’re curious, motivated by the future of technology, and want to be part of a unique and diverse
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to providing education with a purpose and carrying out research which has a positive impact on communities across the globe. Driven by our mission to be the difference, we are addressing real issues, providing
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program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få en oversikt over besøkene dine på
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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mobiltelefonen din. En cookie er ikke et program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få
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data (e.g. DFT, MP2) and experimental data into AI-driven pipelines for structure–property learning and reactivity prediction. Applying AI models to real-world problems in virtual screening, ligand