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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for
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understanding of non-stationary complex systems through theoretical analysis and numerical simulation develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time
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A position exists for a Postdoctoral Research Associate in the Department of Applied Mathematics and Theoretical Physics modelling the decontamination of porous and absorbent material. This project
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collaborative research environment. Education, Qualifications and Experience We are looking for outstanding candidates with a PhD in physics, electrical engineering, applied mathematics, computer science, or a
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are particularly interested in candidates with a strong mathematical background and expertise in one or more of the following areas: High-dimensional probability and concentration/functional inequalities Markov
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to self-organize into complex structures. Our approach is to develop sophisticated mathematical models – informed by state-of-the-art biological knowledge and experimental data – to understand
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. The project seeks to advance population health using innovative quantitative methods in system dynamics computational modeling and structural equation modeling applied to accelerating the translation and
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Postdoc: Geospatial AI Modelling & Uncertainty Quantification of Biomass Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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Join our team as a Early-Career PostDoc (m/f/d) in the research area of AI‑based modelling full-time (39.2 hr/week), fixed term for two years. Leibniz-IWT stands for research in the field of new