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-enhanced exact methods, particularly focusing on Column Generation (and Branch-and-Price), to improve scalability and convergence in solving complex optimization problems. In collaboration with your
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collegial respect and academic freedom tempered by responsibility. We develop talent by offering national/European and global networking opportunities, unique research infrastructures, and a collaborative
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passionate, curious, and driven individual, committed to accelerating the green transition by advancing autonomous solutions for wind power operations. You thrive on solving complex problems, ask bold and
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professional network through international research stays and develop innovative solutions that support the global transition to sustainable energy systems. Apply now to make a difference in the field
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. Responsibilities: Conduct research in time-predictable computer architecture. Designing a network-on-chip for real-time automotive systems Verify the design with modern verification methods, such as function
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, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and
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of Civil and Mechanical Engineering, Thermal Energy Section. We look for a talented, self-motivated, and team-oriented individual who thrives in a collaborative environment and enjoys tackling complex topics
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. Opportunities to participate in conferences, symposia, and networking events to share and enhance your research. Your role will be pivotal in driving AI innovation and contributing to a transformative approach to