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people who have: - A solid educational background, master's degree or equivalent, in electrical engineering, physics or related fields. - Good practical knowledge regarding measurement technology 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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to this pagehttps://web103.reachmee.com/ext/I003/583/main?site=6&validator=e4575239eb8c0828707e2b716f86c5f8&lang=UK&rmpage=job&rmjob=8261&rmlang=UK
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August 2024 Reference number: 2236-2024 URL to this pagehttps://web103.reachmee.com/ext/I003/583/main?site=6&validator=e4575239eb8c0828707e2b716f86c5f8&lang=UK&rmpage=job&rmjob=8207&rmlang=UK
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to this pagehttps://web103.reachmee.com/ext/I003/583/main?site=6&validator=e4575239eb8c0828707e2b716f86c5f8&lang=UK&rmpage=job&rmjob=8249&rmlang=UK
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. Final day to apply: 15 August 2024 Reference number: 2195-2024 URL to this pagehttps://web103.reachmee.com/ext/I003/583/main?site=6&validator=e4575239eb8c0828707e2b716f86c5f8&lang=UK&rmpage=job&rmjob=8160
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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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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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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