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treatment processes through advanced machine learning, validated against physics-based models and experimental data. 2. System Integration: Integrating the DTs into material and energy balance equations
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(immersive reality, planning and simulation models) for joint planning assessment · support demonstrators of the developed prototypes in the project You will be part of a team comprising three PhD
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, patient travel times, regional variations, and treatment patterns. Simulation Modelling: The candidate will develop and apply simulation models to evaluate the effects of centralizing care on measures
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) methods to tackle challenging molecular engineering problems in life sciences and materials design. Situated in the Data Science and AI division, our group advances generative models, molecular simulations
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CFD, turbulence models. Experience in visualizing and analyzing simulation data and interpreting results. Strong written and verbal communication skills in English The following experience will
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challenging molecular engineering problems in life sciences and materials design. Situated in the Data Science and AI division, our group advances generative models, molecular simulations, and molecular design
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found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation Product Development Material Production and in the interaction between these areas. The research covers
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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level in electrical engineering, electromagnetic engineering, wireless engineering, engineering physics, applied physics, a closely related field. Good command of electromagnetic simulation tools such as
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. Empa is a research institution of the ETH Domain. Empa's Laboratory of Biomimetic Membranes and Textiles is a pioneer in physics-based modeling at multiple scales. We bridge the virtual to the real world