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our community. We are now looking for a Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems Are you passionate about developing AI-based and quantum-inspired
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theory and practical algorithms that move reinforcement learning closer to real-world systems. Position 1 will focus on trajectory-centric optimization, Position 2 on adaptive policies, and both will
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fully determine the torsional response using conventional methods alone. Unknown external forces and torsional response can instead be estimated using methods such as convex optimization or Kalman
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successful candidates will develop fundamental theory and practical algorithms that move reinforcement learning closer to real-world systems. Position 1 will focus on trajectory-centric optimization
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sustainability-driven optimization of hybrid multi-material structures. The work focuses on bringing environmental and circularity goals into structural design alongside strength, stiffness, and cost
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sciences, geoinformatics, physics, computer science, or a related field. Strong programming skills, for example in Python or R, are required. Experience with point cloud processing, terrestrial or airborne
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MQS group’s research projects. Our recent work has focused on the theory and applications of quantum walk algorithms, variational quantum algorithms and their optimization, adiabatic quantum
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Engineer in the <b>Center</b> for Interdisciplinary Data Science and Artificial Intelligence Abu Dhabi, United Arab Emirates Senior Strategic Advisor Camperdown, Australia Post-Doctoral Associate in the Division of Engineering (Electrical and <b>Computer</b> Engineering) Abu Dhabi, United Arab...
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machine learning, computer vision, multimodal perception, probabilistic modeling, and interpretable artificial intelligence. The research will be conducted in collaboration with leading national and
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contextual and behavioral cues to understand human actions, anticipate future behavior, and reason under uncertainty. The methodological scope includes machine learning, computer vision, multimodal