Sort by
Refine Your Search
-
to test theoretical hypotheses and identify new regularities; contribute to an interdisciplinary research environment at the interface of physics, epidemiology, and complex systems. This position offers
-
to an interdisciplinary research environment at the interface of physics, epidemiology, and complex systems. This position offers the opportunity to work on a problem where theory, data, and societal relevance meet. The
-
reinforcement learning Enhancing transparency and contestability of decision-making processes, taking a multimodal approach to reveal the reasoning behind complex AI-driven planning and learning algorithms
-
decision-making and reinforcement learning Enhancing transparency and contestability of decision-making processes, taking a multimodal approach to reveal the reasoning behind complex AI-driven planning and
-
underexplored. Rather than functioning as neutral tools, algorithmic models translate complex realities into scores, rankings, classifications, and predictions. In doing so, they shape how problems are defined
-
of research); has experience with large-scale, complex data sets and advanced statistical methods; enjoys doing research and reporting the results in scientific articles; want to share scientific knowledge with
-
Application deadline: 31 January 2026 Apply now Unlock how geographic data can answer complex societal questions: in this PhD you develop semantic and AI-driven models that transform diverse geodata
-
theoretical physics. Particularly important are invariants counting vector bundles (or sheaves) — central objects in modern geometry and physics. However, the theory is mostly developed over the complex numbers