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, incorporating insights from the philosophy of language, the cognitive language sciences, linguistic pragmatics, and formal logic / epistemology. The main task of the post-doctoral researcher is to contribute to a
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propose to combine machine learning techniques with formal methods. We will focus on safe reinforcement learning of motion planning problems for autonomous vessels. Motion planning is particularly
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Max Planck Institute of Molecular Cell Biology and Genetics | Dresden, Sachsen | Germany | about 5 hours ago
Dresden . Your responsibilities: Drive independent and collaborative research in applied topology within the group’s thematic focus. Develop and refine methods to address new mathematical questions
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 8 days ago
and refine methods to address new mathematical questions. Contribute to publications, proposals, and joint projects with internal and external partners. Present and discuss results at seminars and
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derivation, analysis, and comparison of numerical methods and simulation approaches for the solution of PDEs Formal proofs, e.g., for convergence, existence, and uniqueness of solutions Fast prototyping of new
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essentially new methods to automatically verify cyber-physical systems. Because none of the existing methods and tools for the formal verification of cyber-physical systems are fully automatic, these methods
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brings together methodologists (from areas like statistics, computer science or formal demography) with population scientists in order to foster cross-pollination of ideas, to advance methods and theories
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interdisciplinary team. Applicants with strong background in the following fields are preferred: Dynamical Systems Control Theory Formal Methods Machine Learning Context The applicant will be directly advised by Prof
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of results in scientific journals Requirements PhD in Physics, Engineering, Economics, Environmental Sciences, Mathematics, System Sciences or a related field training in formal, quantitative methods
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of results in scientific journals Requirements: PhD in Physics, Engineering, Economics, Environmental Sciences, Mathematics, System Sciences or a related field training in formal, quantitative methods