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element modeling, computational fluid dynamics). Knowledge of heat and mass transport processes in heat-sensitive materials and process optimization. Experience in supply chains and hygrothermal
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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have an interest in detecting and optimizing spray deposition on plants and reduce environmental risk of plant protection products by reducing exposure of soil-water and bystanders? Are you interested
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are carried out in direct collaboration with industry to a great extent. The position is offered in relation to the research program "Power Electronic Control Reliability and System Optimization" and the PhD
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for Mathematics (KdVI) and the Informatics Institute (IvI), as well as Deep Blue Capital. This unique setting gives you the opportunity to combine rigorous academic research with real-world applications in
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Funding: School of Computer Science studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780 per year for 3.5 years. Lead Supervisor’s full name & email
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, enabling multi-vessel charging and scalable maritime electrification. Advanced control strategies and data-driven optimization methods will be considered to enhance the efficiency, sustainability, and
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still hampered by: Ability to detect areas along the intertidal for optimal restoration3. Knowledge on how positive species interactions can be harnessed for rapid restoration4. Availability of devices
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involve parametric and computational design in Grasshopper, physical computing and digital sensing, robot toolpath design and optimization, as well as custom programming in Python or other languages. Your
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their applications to problems in natural sciences (physics, chemistry) and practical computing (machine learning, AI, optimization), and methods to make them compatible with near-term quantum devices