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Field
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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? Information Integrated
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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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new brain stimulation methods, you will contribute to developing closed-loop algorithms for regulating brain dynamics with clinical applications in epilepsy and psychiatric disorders. Number of awards
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limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data
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of the Khovanov–Seidel representation in new cases, using Garside-type approaches. Developing extensions of Garside theory to the case of infinitely many atoms may also be of interest and will rely on the study of
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transparency and trade secret claims of regulated actors? And explore legal arguments in support of algorithmic transparency and data access for public interest research? How does EU law balance transparency and
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performance. Duties and responsibilities include the development of new abstractions and algorithms using computational sheaf theory. Such algorithms will be developed for understanding composite energy-driven
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vision systems (both hardware and software aspects), • development of machine vision algorithms, • support in leading a research team, • participation in teaching activities. Work Location(s) Number
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– depending on the successful candidate’s background and interests. Your tasks: Develop new exact and approximation algorithms and perform complexity analyses for optimization problems on (temporal) graphs
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well as to optimize the tooling geometry. These process simulations require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will: Develop efficient