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Field
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specialist collaborator to guarantee adequate integration of perception and action; advanced motion-planning and control algorithms, continuously refined via robotic digital twins, enable reliable handling
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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may decide to implement a same format slightly differently, leading to irreproducible results, non-portable code, hard-to-find bugs, and other unexpected behaviours. On the backdrop of this complex
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more sustainable? If you share our passion for technology and the difference it can make in meeting the UN’s Sustainable Development Goals, perhaps you are one of our two new PhD students. At DTU Electro
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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for AI based algorithms. Research experience in these areas will be highly valued. The successful candidate will also contribute to the formulation and submission of research publications, development
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scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive
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modeling tools and HDL simulators to validate functionality. Collaborate closely with algorithm designers to co-optimize architecture. Publish results in high-impact journals and conferences. Qualifications
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Ability to work independently as well as in teams. Work in a structured way, set goals and make plans to achieve them, result-oriented. Excellent analytical skills, analyze data, assess different
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scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive