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Field
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science with strong connections to engineering, natural sciences, and industry. About the research project The PRONTO project aims at modeling public transport networks with stochastic partial differential
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of the research field Critical Infrastructure Resilience Knowledge of Collaboration theories Ability to conduct social network analysis, statistical analysis of surveys, or modelling of critical infrastructures
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the aim of developing models, tools and competitive technological solutions to support the transition in sectors such as energy, transport and heavy industry. Within a scientifically excellent environment
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languages (for example, for hardware design or parallel programming) Array or tensor programming Applications to physical sciences, dimensional analysis, or climate impact modeling It is highly meritorious
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learning research. What you will do Propose, develop, and evaluate advanced machine learning models, including reinforcement learning methods, for the energy-aware coordination of EV fleets. Publish high
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Experience in mechatronics and system integration, as well as modelling and simulation of robotic, automation, or production systems Experience in teaching within relevant technical fields Ability
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well as a highly collaborative research environment. For more information about Nathaniel Street’s research group, see: https://www.umu.se/en/staff/nathaniel-street/ Project description Establishing robust