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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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of advanced preclinical in vitro and in vitro models inclucing genetic engineering of T cells to address mechanistic and translational questions relevant to clinical application. Your responsibilities
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 15 hours ago
for Demographic Research, Rostock This network focuses on “scientifically motivated engineering” to design, build, and test digital prototypes—such as machine learning models and large language models—that serve as
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System Modelling group at TUM (https://www.asg.ed.tum.de/esm/home/) and will be closely involved in the Schmidt Sciences project MountAInWater, coordinated by the Institute for Science and Technology
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | about 1 month ago
power to support the ambitious theoretical, modeling, and data-driven objectives of the proposed work. Job requirements Applicants should hold a PhD in biology, physics, engineering, or a related field
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location: Rostock Deadline: 17.03.2026 Join the Cluster of Excellence “BlueMat: Water-Driven Materials” (www.tuhh.de/bluemat ) and contribute to one of Europe’s most exciting research initiatives
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competitive research in AI-driven semantic analysis and automated reasoning-flow modeling, with applications to educational materials, scientific documents, and research authoring. Your work will focus
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methodologies. The focus is on across-organ imaging, ranging from non-human primate (NHP) models to human applications. You will contribute to the development and application of state-of-the-art MRI techniques
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of hydrological connectivity of soil moisture using gridded soil moisture data sets and data-driven approaches (e.g., complex network methods) Develop models to predict gatekeeper locations and their relationship
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human-robot-teams