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opportunity to work at the forefront of brain-inspired control and soft robotics. At DTU, you will develop novel control architectures that combine model-based methods, reinforcement learning, and
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and model-form uncertainty. Approximately half of the effort will extend this framework to the constitutive modeling of porous and cellular materials, such as polymer and metal foams, and to industry
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-grain 3D integration, advanced packaging, backside power delivery networks, and chiplet-based architectures require new methodologies to model and optimize system behaviour beyond the traditional
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virtual platform for testing and optimizing innovative Raney electrode design concepts. The simulation results will deepen the theoretical understanding of electrode processes, particularly for water
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. Experience in particle physics, in particular with collider simulation tools (e.g., MadGraph, Pythia, Delphes), statistical analysis of LHC data or beyond-the-Standard-Model phenomenology, is meriting
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, involving the development and refinement of Monte Carlo simulation generators to accurately model neutrino interactions with various target materials. Detailed comparisons of these simulations to data
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modeling and simulation, process control, or model-based analysis is a plus. Experience with industrial automation, manufacturing systems, data acquisition, or related technologies is a plus. Strong
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and machine learning, including applications to global analyses, as well as quantum information, and real-time classical and quantum simulation. For more information, please consult https
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evolves. Leadership (10%) The Director of Ultrasound Education contributes to the strategic and operational leadership of the BSOM Simulation Program. Responsibilities include: Serve as a role model for
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contributing to government, defense, or security ‑ related R&D programs (internships, fellowships, or full ‑ time roles). Familiarity with simulation ‑ based models (e.g., physics ‑ based, network