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within ongoing and new research projects; contributing to both fundamental understanding and applied innovations aimed at sustainable chemicals, materials, and processes; collaborating within
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process. This project offers a unique opportunity to work at the intersection of machine learning and control theory. You will develop rigorous theory and scalable computational methods for certifying
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hydrological processes, aquatic ecology and biodiversity, microbial ecology as well as on environmental chemistry and aquatic ecotoxicology. The department has about 150 employees, of which approximately half
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December, you will be asked to prepare a short research proposal. You will preferably start your employment on 1 March 2027. We can imagine you're curious about our application procedure . It describes what
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engineeringEducation LevelBachelor Degree or equivalent Research FieldMathematicsEducation LevelBachelor Degree or equivalent Research FieldPhysicsEducation LevelBachelor Degree or equivalent Research FieldComputer
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on the ventilation process, which typically considers the use of window and mechanical air treatment based on average climate measurements. Airflow affects crop transpiration, growth, development, yield and quality
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
application process here. About the position The Department of Department of Mechanical and Industrial Engineering is offering an exciting PhD position within the Norwegian Maritime AI Centre , a national
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employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position Are you motivated to take a
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their job search in the Netherlands. Additional information For more information about this vacancy, you can contact Dr Jaco Quist ([email protected] ). Application procedure Are you interested in
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Postdoctoral Researcher to lead technical service delivery for the Luxembourg Digital Innovation Hub (L-DIH 2.0). Operating at the intersection of process systems engineering, data-driven modeling, and applied