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optimize project frameworks, drive collaboration across pilot line partners and leading tech companies, and turn innovation into real-world impact. Working at the heart of Europe’s semiconductor ecosystem
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natural resources of these areas. The Research Professor explores and develops solutions that use Arctic natural resources in an economically, ecologically, socially and culturally optimal way that enhances
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computational resources, including an upcoming pan-European AI-optimized supercomputer (available by 2027), and An international workplace, with English as the working language. We are strongly committed
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processed by advanced and sustainable manufacturing, integrated in the circular economy. The starting point in modern production at M2P is digital data, generated and optimized. Research methods encompass
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(land, aerial, marine, or hybrid) Distributed decision-making, task allocation, and worksite optimization under uncertainty Energy-aware and resource-efficient collaboration strategies for fleets
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, human-centric systems, and technology deployment. Your research may focus on any of the following themes or a combination thereof: -Design, optimization, implementation, ramp up, and operation of
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-scale simulation, signal and image processing, time-series analysis, optimization and control, computational inverse problems, and artificial intelligence methodologies. The field of teaching is
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for improving knowledge in design, optimization and decision support for novel and sustainable construction materials. The candidate should also possess demonstrated experience in the area of AI/ML and concrete