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postdoc. For this position, we are looking for a PhD candidate eager to deal with the understanding of the diverse values of nature (including biodiversity and ecosystem services) across stakeholders, and
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. The first one will advance techniques for large-scale 3D particle tracking by merging measurement theory and practice with flow modelling for applications in industrial wind tunnels for the aerospace sector
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traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where possible. This innovative new approach enables more efficient and
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chemistry and study the physicochemical properties of peptides loaded into the materials. Build surrogate models and apply machine learning techniques to extract design rules and rapidly screen thousands
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(based on fulltime) and extra holidays between Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; multiple courses on topics such as leadership for academic staff
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to develop a new generation of traffic prediction methods, combining traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where
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scholarships and some postdoc positions. More information can be found here: Norwegian Maritime AI Center. Duties of the position Conduct research on trustworthy agentic AI built on open-weight foundation models
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
processing data streams, with theories and methods for planning and logistics. The PhD research will focus on AI-enhanced planning of operations in shipbuilding supply chains, examining how AI techniques can
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
of AI is both a technical and an integrative challenge. It requires combining what AI excels at, such as pattern recognition and processing data streams, with theories and methods for planning and
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Willingness to combine wet-lab experimental work and computational analysis Basic knowledge of statistics and/or programming (R, Python, or similar) Strong motivation to learn new techniques across