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Field
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Are you fascinated by electromagnetic modeling and numerical problem solving? Do you want to contribute to the development of state-of-the-art metrology for integrated-circuit production
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
. Such structures can be used to construct artificial cell mimics and new materials. A scaffold-free DNA tile assembly is a programmable method for the formation of two- and three-dimensional DNA structures which
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associated numerical methods and AI, will be used with High Performance Computing (HPC) to improve understanding of key flow physics and inform future HPT design. Skills and Experience Required: Applicants
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profound interest in inorganic chemistry, both in experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work
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not exclusively deploy qualitative IS methods, with specific focus on case study research, taxonomy-building and design science research, as well as to conduct interviews with relevant stakeholders
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not exclusively deploy qualitative IS methods, with specific focus on case study research, taxonomy-building and design science research, as well as to conduct interviews with relevant stakeholders
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, and a solid understanding of numerical analysis and familiarity with the use of analytical tools. They should also have knowledge and experience in parallel coding and spectral methods. They must have
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not exclusively deploy qualitative IS methods, with specific focus on case study research, taxonomy-building and design science research, as well as to conduct interviews with relevant stakeholders
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not exclusively deploy qualitative IS methods, with specific focus on case study research, taxonomy-building and design science research, as well as to conduct interviews with relevant stakeholders
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of invariants of operator algebras, such as K-theory and cyclic homology; and Developing a mathematical method for passing from numerical Berry curvature to robust topological invariants in a large class of cases