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are to: Build a value chain decision-making tool based on mixed-integer linear programming Develop sensitivity and uncertainty assessment algorithms to assess various scenarios in a biofuel value chain Support
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++) Knowledge of the fundamentals of ML/AI algorithms for communications and networking, and their implementation A creative mindset and curiosity to research and develop new solutions with highly skilled
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
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. Experience with phase retrieval algorithms, clean room use and e-beam lithography are beneficial. The candidate will be expected to participate at international user facilities and thus will be expected
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Tenure-track Assistant and Associate Professorship positions in Data Science and Machine Learning...
, the position can be at our established campus in Odense or at our developing new campus in Vejle. What we are looking for We are looking for new colleagues who can strengthen or add to our competences in
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of Geodesy and Earth Observation (GEO). In this position, you will develop algorithms and methods aimed at improving GNSS position integrity and mitigate/reduce both natural and intentional signal interference
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of individual development. The group is involved in a variety of national and European projects and features a strong network of academic and industrial partners. We solve challenging research problems
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to ensure that the developed notations and algorithms address the companies’ needs. More about the related project can be found here: https://innovationsfonden.dk/da/news-article/ai-skal-forudsige-og-forklare
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by: Developing specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in