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Field
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-analytical workflows, turning geodata into new answer maps. We use knowledge graphs to model these transformations and apply AI methods to scale them across large map repositories, enabling users to explore
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should have a strong mathematical background, particularly in dynamical systems theory, and a keen interest in network science, and scientific computation. The student will gain invaluable experience
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model development, robustness, and long-term reliability. What you can expect Modelling. Apply probability theory, statistical analysis, and machine learning techniques to build robust models and generate
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transitions and requires an interest in both theory development and engagement with practice. The PhD position is part of the larger AMBITIONS project involving TU Delft, Utrecht University, and Avans
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powerful ideas and tools at the intersection of topological band theory, symmetry analysis, and photonics. You will work on developing and applying these ideas to discover new topological phenomena, design
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Degree Doctor of natural sciences (Dr rer nat) Doctoral degree or degree awarded by University of Bonn Course location Bonn In cooperation with Bonn International Graduate School of Mathematics
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interdisciplinary research and training program. The objective of the open PhD position is to advance current over-the-air-computing (AirComp) approaches for federated and graph-based Embedded AI to account for
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University of Innsbruck, Department of Mathematics Position ID: 3366 -PHDPOSITION [#26832, MIP-15291] Position Title: Position Type: Non tenure-track faculty Position Location: Innsbruck, Tirol
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decision-making, and mathematical theories of AI. While applications of AI are used to validate these innovations, the primary goal is to build foundational methods and theories for societal impact. Course
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of precision fermentation or cell culture - Affinity towards technical tasks and bioprocess control - Advantageous: Experience in mathematic modeling, programming, CAD, microfluidic or bioreactor systems