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Stig Brøndbo 4th August 2025 Languages English Norsk Bokmål English English Faculty of Engineering Science and Technology PhD Fellow in signal processing and modelling in the seafood industry Apply
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for a Postdoctoral Fellow, full-time in a 3-year position. Postdoctoral applicants must hold a PhD degree in computer science, telecommunications or electrical engineering at the start date
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such as transportation, healthcare, and telecommunications, making batteries a cornerstone of sustainable development and technological progress. Battery digitalization is critical for accelerating
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master's degree of 300 ECTS. All applicants should have a grade point average of B (or equivalent) on their master’s degree in order to be admitted to the PhD programme. The grade point average also applies
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hold more than one fixed term position as a Postdoctoral Research Fellow at the same institution. Unless special circumstances indicate otherwise, postdoctoral projects shall be planned with stays abroad
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engineering and science, as well as PhD education in computer technology. The Mohns Center for Innovation and Regional Development researches innovation and offers master's education in innovation and
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PhD Research Fellow in Chemistry-focus on Experiments in Chemical Kinetics and Heterogeneous Catalys
description The transition from a fossil-based to a circular production of consumer goods requires the development of new chemical processes, especially for the energy-efficient and sustainable conversion
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PhD Research Fellow in Chemistry-focus on Experiments in Chemical Kinetics and Heterogeneous Catalys
description The transition from a fossil-based to a circular production of consumer goods requires the development of new chemical processes, especially for the energy-efficient and sustainable conversion
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) and a reasoning of the choices. It should also indicate the methodologies to be used. The final project description will be developed in cooperation with the supervisor. The understanding of production
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interdisciplinary team will develop a machine learning based monitoring system that leverages spoken language processing (SLP) and natural language processing (NLP) of speech recorded at home to calculate relapse