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Siri Pedersen 9th August 2026 Languages English Norsk Bokmål English English PhD Fellowship in Data-Driven Optimization of Multi-Energy Systems Apply for this job See advertisement Job description
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for 3 years. Responsibilities The successful candidate will: Develop, optimize and validate advanced 3D cell culture models, including spheroids, organoids and tissue-engineered constructs. Establish
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welding routes. Therefore, the main tasks of the position are as follows: Process Parameter Development: Development and implementation of optimal arc and solid-state welding characteristics Monitoring
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photovoltaic generation, hydrogen production, and storage alternatives with microgrid-driven power distribution. Through advanced modelling and optimization techniques, this research aims to identify optimum
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of educational competence required for an Associate Professor position. The appointment is for 3 years. Responsibilities The successful candidate will: Develop, optimize and validate advanced 3D cell culture
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include, but is not limited to, UHPC material design and optimization, durability testing under harsh environmental conditions, fabrication and full-scale structural testing of sleepers under static and
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and validate railway sleepers made with UHPC. The work may include, but is not limited to, UHPC material design and optimization, durability testing under harsh environmental conditions, fabrication and
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ecosystems where interconnected multi-agents interact strategically in dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently
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surgery. However, the growing use of TAVI has also increased the need for accurate methods to assess valve disease, identify patients who will benefit from intervention, determine the optimal timing
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, state drift, read disturbs and non-linear multi-state programming. This PhD project aims to address these issues by fabricating and characterizing ReRAM cells optimized for balanced ternary (symbols -1, 0