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Your Job: Investigate current challenges and bottlenecks in power flow analysis for large scale electrical distribution grids Apply machine learning/AI or surrogate modeling (e.g., neural networks
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research school on secure distributed computing (SeDiC) is proposed. SeDiC aims to tackle the challenges of exchanging and computing data across a network of interconnected systems. It addresses scalability
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flow”, which is one sub project in the European Training Network COMBINE, where a total of 17 PhD positions are available at the premises of 14 European institutions from academia and industry: https
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Infrastructures Didactics of Informatics Digital Humanities Distributed Systems High-Performance Storage Machine Learning Medical Informatics Neural Data Science Practical Informatics Scientific Information
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: Fail safe, Distributed Digital Twin for Innovative Air Mobility (IAM) Operations Supervisor: Prof. Dr. Uwe Assmann, Chair of Software Technology and co-supervised by at least one
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promising lean alloy system for additive manufacturing, as the mechanical properties can be tailored through phase composition, distribution and morphology by tuning process parameters. The work is carried
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-off companies. For this, we conduct research with our approximately 1,300 staff across four focus areas: energy provision, energy distribution, energy storage, and energy use. Fraunhofer ISE's state
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institutions from academia and industry: https://euraxess.ec.europa.eu/jobs/401249 . Your mission The aim of the project is the development of a physical model of the initial solidification of steel during
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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configurations (residential, commercial, mixed-use) and their interactions with distribution grids Assessing how renewable integration, storage technologies, and demand flexibility affect system performance