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Organisation Job description For the National Growth Fund (NGF) project “Groeien met Groen Staal” (GGS), a PhD position for the period of 4 years is available in the context of modelling green steel
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the optimisation strategies to enhance the performance of complex machine learning models such as deep learning model and large language model. Applicants need to have strong background and track records of research
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Specifications. The PhD topic consists of two parts, the weighting of which can be adjusted. First, natural frequencies of different UAV categories for different power settings shall be modelled. Second, based
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frequencies of different UAV categories for different power settings shall be modelled. Second, based on mesoscale fluid dynamic simulations, microclimatic and turbulence modelling procedures in urban
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University, you will build models and methods to parse natural language questions into geo-analytical workflows, combining NLP and semantic representations to improve how complex spatial questions can be
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. The core objective is to develop advanced 3-D modelling and optimisation methodologies for magnetic components that enable accurate leakage inductance prediction and improved overall performance. Traditional
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measurements taken from numerous platforms. Data processing takes place at the AERIS national data centre, part of which is integrated into the IPSL. Mission: This project will assess the local cooling potential
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for effective water resource management, climate modeling, and agricultural planning. Despite its importance, accurately monitoring evaporation remains a major scientific challenge due to the complexity
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will lead the development of novel motor topologies optimised for this cutting-edge material. Supported by experienced supervisors, the student will be able to design, model, and validate working
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get exposed to a multitude of technologies including nanofabrication, optics, spectroscopy, data analysis, and numerical simulations. Working, teaching and research at ETH Zurich We value diversityIn