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to efficiently biofuctionalize multiple flexMEA chips in a single run Optimize the design of flexMEA chips to improve the performance of our in-house portable electronic measuring device Support the
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scientists. We seek to appoint an expert in the research area of Machine Learning for Sustainable Processes and Materials with a focus on data-driven methods for modeling, analyzing, and optimizing complex
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of error mitigation and error correction primitives. Thereby, the applications of quantum computing that this group is working on is diverse, ranging from various machine learning methods over optimization
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optimize material properties such as conductivity, adhesion, and impermeability through methods like sintering, crystallization, and melting. One focus of our research is printed electronics, where we
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fundamental investigation, optimization and development of photoreactors from laboratory to industrial scale as well as advanced reaction control as a basis for the development of sustainable photochemical
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compensate for the influence of hardware errors, you will identify optimization potentials and implement the latest error mitigation strategies. Your area of responsibility also includes applying
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) - Thesis “Optimization of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) Reactions on Microarrays” Duration: 6 months We are looking for a talented and motivated student specializing in
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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity
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management of factory operations. Based on many years of expertise in robotics, operational optimization and control systems, the Automation Technology division is opening up new fields of application
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disabilities, we work together to find solutions that optimally promote their abilities. The same applies if they do not meet all profile requirements due to a disability. With its focus on key technologies