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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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structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We will consider techniques like flow matching, and use ideas from optimal
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modelling and optimization techniques, this research aims to identify optimum design and operational strategies that enhance system flexibility, improve resilience to variable supply and demand, and minimize
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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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utilize low-grade waste heat. The project aims to develop methods for the design, optimization, and operation of integrated systems that maximize both economic performance and environmental benefits
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utilize low-grade waste heat. The project aims to develop methods for the design, optimization, and operation of integrated systems that maximize both economic performance and environmental benefits
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. This highly innovative project aims to develop a fully AI driven digital twin that enables real-time optimization and control of fermentation processes. The candidate will develop the digital twin for microbial
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to the development and delivery of high‑quality education Research – Conduct independent and collaborative research on topics such as hydraulic network modelling and optimization, infrastructure resilience and risk
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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