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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make energy districts and communities more sustainable? We are looking for a highly motivated and
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contribute to the teaching activities of the section of Mechanical Engineering by teaching 1-2 courses per semester. You will focus on developing and extending in-house computational codes based on open-source
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industrial and academic partners. The overall goal of the project is to optimize the design of water eletrolyzers for efficient green energy production. You will be conducting Computational Fluid Dynamic (CFD
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, holistic planning and scheduling to optimize resilience across several factory systems. Development of AI-based tools and complex simulation systems is expected to be a core contribution. 3) IT and OT