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master student projects within the master program in Sustainable energy engineering. Qualifications You are qualified to apply for this position if you have an MSc or equivalent degree in Environment and
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state-of-the-art research. You must have a master's degree in computer science or similar subject. Experience with machine learning, Deep Learning and statistics is required. You must have good knowledge
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Limited, UK (regarding beam shaping solutions). The mobility periods of each PhD-student are integral part of this EU funding scheme. Duties Your main tasks will be to perform experimental and theoretical
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"GreenCarbon4Steel - Tailoring Green Carbon for Steel Industry”, funded by the Austrian Research Promotion Agency. The project is led by BEST – Bioenergy and Sustainable Technologies GmbH and LTU is one of the main
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"GreenCarbon4Steel - Tailoring Green Carbon for Steel Industry”, funded by the Austrian Research Promotion Agency. The project is led by BEST – Bioenergy and Sustainable Technologies GmbH and LTU is one of the main
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are looking for committed people who have: -A solid educational background, civilingenjör or master's degree or equivalent, in electrical engineering, physics or related fields. -Knowledge of programming in
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of this project is to use life cycle assessment (LCA) as a main tool to identify where in the steel’s material value chain the greatest environmental impact lies. The assessment can be used as a tool to
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, must be written in English or Swedish. Closing date for applications: 26 May 2024 Reference number: 1803-2024 URL to this pagehttps://web103.reachmee.com/ext/I003/583/main?site=6&validator
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application with the reference number below. Closing date for application: 16 April, 2024 Reference number: 1412-2024 URL to this pagehttps://web103.reachmee.com/ext/I003/583/main?site=6&validator
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application with the reference number below. Closing date for application: April 16, 2024 Reference number: 1411-2024 URL to this pagehttps://web103.reachmee.com/ext/I003/583/main?site=6&validator