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tools for the prediction of composite manufacturing processes. You will work on development of algorithms, custom written codes, application of commercial finite element software and development of user
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candidates will have specialist knowledge in signal processing and algorithm design, with experience in machine learning, AI system development and reinforcement learning along with a strong publication record
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algorithms (such as machine learning or clustering). Familiarize with the multi-level data and how to model them in a polystore architecture [2] or similar (Month 1 – 12). Develop an environment to test the
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: Design hierarchical models that explicitly capture misspecifications in metabolic models Develop differentiable and scalable inference algorithms using automatic differentiation Implement HPC-tailored
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description: Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use
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. The ultimate goal is to develop theory and methods for the construction of low-complexity invariant sets, using computationally tractable algorithms. Funding Notes This is a self-funded research project. We
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data from public or commercial databases and develop algorithms using existing libraries. Based on the previously identified resources, the Ph. D. thesis will then focus on the extraction of oxides and
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Technology, Dep. ETI / Embedded Systems, we are looking for a researcher as of the 01.04.2026. Your tasks: Development of architectures and algorithms for adaptation of time-triggered systems based
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disease patients using radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical
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year. The P2S2 project aims at developing parton-shower algorithms with unprecedented (logarithmic) accuracy for jet substructure at the LHC. The project also has connections with analytic resummations