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Field
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and responsibilities: The researcher will be in charge of supporting the development and optimization of nanomaterial-based biosensing platforms for biomedical applications. The researcher will
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renewable energy use, energy security, and the reliable operation of hydro-dominated power systems. The project will focus on how AI can support advanced optimization models for hydropower and energy-system
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energy transitions at local, national or global scales. Energy Engineering is a part of the Division of Energy Science in the Department of Engineering Science and Mathematics, which is a subject-wide
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-time operation. The project will focus on how AI and mathematical optimization can be combined to support sequential bidding decisions under uncertainty. The initial use case will consider a wind power
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its inverse reconstruction. A key challenge is the data-driven design of the experimental setup: exploring how the choice of measurements and configurations can be optimized to extract the most useful
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with a strong background in applied mathematics, control theory and/or optimization to apply for a fully funded 4-year PhD position in the Smart Manufacturing Systems (SMS) group at the Engineering and
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, computer engineering, computer science, data science, mathematical engineering, robotics, or a closely related field. The candidate should have solid mathematical and analytical skills and a strong interest
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methodologies for assessing Local Energy Communities. Contribute to the integration of market and economic considerations into mathematical optimization models. Analyze electricity market structures, pricing
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research covers a wide range of topics from radiobiology, radiation physics and space research to radiation therapy. The radiobiologic modelling group focuses on developing strategies and mathematical models
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of the position) a MSc degree in computer science or a closely related field (e.g., mathematics) - The selected candidate is interested in declarative problem solving, combinatorial optimization, knowledge