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computational biology with a focus on developing new and scalable computational models (e.g. deep learning, machine learning, optimization or statistics) or integrating data-driven applications to address
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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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to development projects. Establishing a research program in translational computational biology with a focus on developing new and scalable computational models (e.g. deep learning, machine learning, optimization
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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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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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finite-element simulation and topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks above, the
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driving the integration of methods in artificial intelligence (AI) and machine learning (ML) to improve and optimize workflows when developing therapeutic antibodies Duties – what we expect from you As an
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and development centre – an excellent infrastructure to develop and optimize membrane processes from lab to pilot scale. The project is part of COMPEL. COMPEL, "COMPetence for the ELectrification
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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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Subject description Mathematics in a broad sense, which also includes mathematical statistics, numerical analysis and optimization theory. Duties As an associate professor within the framework