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formal methods. The successful candidate will contribute to advancing data-driven modeling techniques that enable formal safety guarantees for complex dynamical systems such as autonomous vehicles
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methods We offer A dual PhD degree at the Universities of Oldenburg and Groningen (for four years) Well-structured, enthusiastic and supportive advising towards PhD completion Being part of a unique
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22 Apr 2026 Job Information Organisation/Company Max-Born-Institute Research Field Physics » Optics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Jun
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25.03.2026, Academic staff Applications are invited for a fully funded PhD position exploring the intersection of reinforcement learning, space-craft dynamics, and formal verification within
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of nonlinear PDEs or the development of new solver- or coupling-methods incl. their convergence analysis, but also modeling and simulation aspects across a wide range of fields - from biomechanics and geophysics
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problems thereby achieving productive and meaningful progress. Method Courses: In method courses, PhD students learn up-to-date methods directly linked to the individual PhD project. Summer Academy: In
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cues. We are looking for a curious, self-motivated PhD student to join this research at one of Europe’s leading primate neuroscience institutions. The start date is 1st of May 2026; a later starting
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Max Planck Institute for Comparative Public Law and International Law, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 1 month ago
, and contribute to joint projects, publications and academic events. There are no formal teaching requirements attached to this position. Profile and requirements A completed PhD in law or political
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biophysics. The work spans theory, experiment, and communication — and we need someone who is willing to engage with all three. The research centers on the Quantum Blueprint Formalism (QBF), a foundational
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the phenomenology of cognition (e.g. formalizing concepts such as reasoning, agency, meaning, or experience into testable computational models, skill acquisition, and affordances). The successful candidate will bring