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comfort at the building and urban scale. One of the group's pillars is research and application of Urban Building Energy Modelling (UBEM) to generate knowledge about cities and neighbourhoods as
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dedicated experiments (e.g., flares vs. chaff). Providing observational constraints on turbulence and thermal effects to improve the representation of microphysical processes in model simulations
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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
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an interdisciplinary team and participate in collaborating with other PhD and Postdoc members. The position will be held in the Microbial Physiology and Resource Biorecovery laboratory (MICROBE) led by Dr. Wenyu GU
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for blockchain-based systems. Develop mathematical and computational models for simulating and analysing various economic properties of blockchain-based systems. Design and evaluate token economies and governance
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) to develop an accurate, stochastic multibody simulation model. This model dynamically updates key parameters to predict effective braking and acceleration capabilities, complementing existing organizational
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multidisciplinary team and use state of the art methods such as Nanoindentation, Raman Spectroscopy, Digital Light Processing, Two-Photon Lithography, Electron Microscopy, and Numerical Simulations. Your research
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related field, and will have experience with one or more of the following: agent-based simulations, system dynamics, mathematical modelling, probability theory, risk assessment, R, python and GIS. Good
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to muon g-2 from lattice Quantum Chromodynamics and algorithmic developments for multi-level and RG-improved simulations (research group of Urs Wenger) C.) Study of multi-hadron systems, with a focus on
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challenges. Our core research topics include but not limited to the following topics: Interpretability and explainability of AI models in clinical settings Fairness and bias mitigation in pediatric AI