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, visualization, rendering, modeling, interaction, simulation, game technology, and immersive environments, with strong connections to artificial intelligence, data science, AR/VR, 3D computer vision, and high
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. Experience with the modeling, simulating and building experimental setups related to one: Batteries SoX, AC and DC Grids, EV charging. Excellent English language skills Experience with managing large projects
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Particle Motion. The project includes nanoswitch design, sensor fabrication, sensor testing, and modelling. The longterm goal is to enable multiplexed continuous real-time sensing for applications in
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industry. Our group combines precision experiments, advanced imaging, and modeling to uncover the physics of tin droplets under extreme conditions of laser irradiation. We have established a strong track
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made large-scale models available to the public, which enables the integration of AI in everyday objects and tasks. As a result, the model scale is doubling yearly, causing a proportional increase in the
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, sustainability objectives and future uncertainties into a unified decision-making framework. The candidate will develop probabilistic modelling and stress-testing approaches, including Monte Carlo simulations and
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, interviews, backcasting, transition pathways, policy mixes, social simulation modelling, and possibly participatory value evaluation or gamification. You will collaborate with other early-career and senior
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limited, noisy, and low-resolution measurement data? In this project, you will develop a novel physics-informed machine learning approach that integrates physical simulations of the measurement process with
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: Developing a system-theoretic framework that models learning as the feedback interconnection between continuous-time circuit dynamics and optimization algorithms. Designing novel energy-based learning
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molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry partners. Job description At TU Delft, you will contribute to a transformative research