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urban catchments. Develop road designs that optimize water accumulation or flow. Create a framework for the selection and design of climate-adapted roads. The research will primarily involve hydrological
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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evaluation frameworks and/or the development of energy system optimization models. The research is applied and closely linked to industrial interests and needs. About the research Our research aims to provide
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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automated planning, reinforcement learning, logic or combinatorial optimization. Furthermore, candidates should have excellent study results, very good programming skills and high proficiency in oral and
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to provide valuable evidence to guide policy and optimize care across the continuum for ageing populations. Work Duties The main task of the doctoral student is to pursue doctoral education in the field
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in multilayer electronic devices -Identifying/optimizing novel polymers and photosensitive materials for additive manufacturing -Developing femtosecond/picosecond laser-based micro-drilling and
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the applicant: - For the dissertation and the subject relevant knowledge and skills, for example demonstrated strong background knowledge at advanced level especially related to automatic control, optimization
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principles as well as material properties of extremely thin silica membranes. In this project, you as a PhD candidate will carry out: detailed theoretical studies and optimization of light guidance in HCFs
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successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor