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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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master's degree (or equivalent) and PhD in Mathematics/Statistics/Data Science Research expertise in the analysis of complex systems Familiar with network analysis, concepts of resilience (e.g. adaptive
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closely with the Department of Mathematics at Aarhus University. In addition, your organic chemistry skills will be instrumental in developing antioxidant artificial cells. These interdisciplinary projects
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analysis with practically motivated case studies, offering a strong foundation for researchers interested in advancing the mathematical understanding of geometric deep learning. Your Qualifications PhD
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contact both, and Your profile PhD in Information Systems, Computer/Data Science, Software Engineering, Applied Mathematics, or a related field Experience in publishing high-quality research, as
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) analysis Mathematical modelling Microbiology Molecular biology We approach science with the view of physics, aiming to identify principles behind complex systems. We collaborate closely with engineers
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schizophrenia. Preference will be given to applicants who have received their Ph.D. degrees in computational neuroscience, physics, mathematics, computer science, or related fields within the last 3 years and
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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). Applicants with a PhD in a quantitative field (computational biology, bioinformatics, systems biology, genetics/genomics, statistics, mathematics, computer science, or related fields) are encouraged to apply