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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 3 months ago
Developing computational framework for 3D shape modeling towards biological insights Developing AI-based representation learning framework for data-driven cell modeling Report findings and methods in
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offers ubiquitous coverage and reliable mobility, whereas optical wireless communication provides fiber-like capacity, ultra-low latency, and immunity to electromagnetic interference. Rather than treating
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international secondments, network-wide training events, and interdisciplinary research activities Acquire highly sought-after expertise in microfabrication, photonics, materials science, and optical sensing
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applications based on the following skillsets. If you do not fullfil all requirements, please still apply (there is room for learning-on-the-job). An engineering degree, preferably, aerospace or mechanical
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results. ● Deploy the results developed in the first stage to linear value function estimation problems in reinforcement learning theory. Establish the foundations to generalize the results to non-linear
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applicability. By bridging machine learning, behavioural science, and clinical research, the project seeks to establish foundational methods for trustworthy agentic AI systems that can be deployed across diverse
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skills. Fluent in English, both spoken and written. Willing to learn the Dutch language. TU Delft (Delft University of Technology) Working at TU Delft means contributing to solutions that really make a
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independently. Good communication skills. Fluent in English, both spoken and written. Willing to learn the Dutch language. TU Delft (Delft University of Technology) Working at TU Delft means contributing
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Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of the Leiden Institute
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of autonomous mobile robots (AMRs) and automated guided vehicles (AGVs) is transforming modern manufacturing, warehousing, logistics, and smart factory environments. Accurate indoor positioning remains a critical