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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
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ships, such as combustion engines, fuel cells, and hybrid or electrified drivetrains. Experimental and modeling activities related to energy converters, fuel sustainability, and environmental impact
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technology, also documented experience of technical programming in e.g. Python or Java are a merit. Experience with modelling and simulation in stormwater management are an added advantage. assessed ability
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KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Project description Third-cycle subject: Computer Science This project involves generative modeling
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study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research group Our lab is advancing precision medicine through deep learning models
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from automated vehicles (AVs), they must be both safe and appreciated by drivers. This project uses modeling (e.g., AI/machine learning) and human behavior data to predict perceived safety and quantify
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importance, for triggering shallow landslides in sensitive clays. The focus will be on developing computational models that will quantify the mechanisms, precursors and the time to failure. This will be
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carbon and greenhouse gas fluxes into this model, and validate it against observational data. Through numerical simulations, you will assess the impact of various parameters on fluxes and use machine
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description We are seeking a PhD student to join our research team specializing in the analysis and modeling of multiphase flows. The research focuses on developing a fundamental understanding and numerical
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interfaces. About us The Condensed Matter and Materials Theory division models and studies diverse materials and condensed matter systems, often inspiring new materials, technologies, or structured media with