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Field
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understanding of intersectoral scientific fields ranging from optical fibre communication design and implementation, components fabrication, artificial intelligence, or techno-economic analysis, which represent
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-time studies, for up to a maximum of 3 years. Scholarship Details Maximum number awarded 2 Eligible courses Any HDR student wishing to study in the field of artificial intelligence Eligibility criteria
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
geometry, algorithmic complexity, and combinatorial optimization. Our contributions are regularly published in top venues like the Conference on Artificial Intelligence (AAAI), the Symposium on Algorithms
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range of science and engineering disciplines, from classical disciplines such as mathematics, astronomy and mechanical engineering, to interdisciplinary fields such as artificial intelligence,nanoscience
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, engineering, mathematics or a related field of study Huge interest in data science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in
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(Computational) Linguistics, Education, Artificial Intelligence or a related field; The skills and knowledge for in-depth automated text analysis and the development and use of text quality metrics; The skills and
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drug design” is led by Docent Juri Timonen, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug
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and/or interest in the following relevant fields: artificial intelligence and cybersecurity. The candidate will have the opportunity to work on a collaborative project with a leading industry in
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Description We are looking for a PhD-candidate interested in topics that lie on the border of optimization by the use of heuristic algorithms and (Explainable) Artificial Intelligence ((X)AI). Specifically, in
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Your Job: As a PhD candidate you will develop and deploy an artificial intelligence (AI) driven approach to streamline high-throughput experimentation (IMD-3: Institute of Energy Materials and