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applicants will take place from March to April 2026. Awards for intake 2026 will be finalised by July 2026. Supported Areas for START Engineering Energy Resilience: Power electronic converters for distributed
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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the spatial distribution of chemical compounds using magnetic resonance at high magnetic fields. The developed chemical imaging approach will be applied both (i) in medicine and biology to monitor
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. The project’s overarching goal is the development of digital quantum algorithms for the simulation of non-abelian lattice gauge theories. We are looking for highly motivated individuals, with the desire
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for Basic Research in Program Verification (CPV) include: extensions of higher-order concurrent separation logics (such as our Iris logic, see iris-project.org ), e.g., to reason about distributed systems
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algorithms into an existing framework, with a focus on efficiency, as well as creation and execution of relevant simulation pipelines: from real data to mathematical and clinically actionable results
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that algorithmic parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but
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2026. Awards for the 2026 intake will be finalised by July 2026. Supported Areas for START Engineering Energy Resilience: Power electronic converters for distributed energy resources and microgrids; High
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience
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• Integrated sensing and communication: fundamental limits and algorithm design (1 PhD, Mari Kobayashi, mari.kobayashi@tum.de) • Optical fiber channel modeling, receiver processing, and coding (1PhD, Gerhard