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Location EAC, Porz-Wahn, Germany Our team and mission The CAVES and PANGAEA team specialises in training programmes that equip astronauts and mission developers with scientific, expeditionary and
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well as develop new algorithms for inverse scattering. These extensions will be employed in a reconstruction process on actual measured data from real-world metrology, in line with the long-term vision presented in
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of this project is to develop techniques that will enable gate-based quantum optimization algorithms to tackle realistic (large-scale, mixed-integer, and constrained) instances of stochastic programming problems
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. The goal is to develop a language-agnostic verification approach, following on promising results related to the Solidity language. - While our current digital infrastructure relies on classical networks
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work hands-on with clinical data and build robust deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image
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In this role, you will help develop and implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical
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ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g., high performance
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developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative machine learning solutions to optimize
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. Your work may involve formulating new models, analysing structural properties, and developing innovative algorithms with both theoretical rigor and practical relevance.
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millions of US Dollars. Ensuring that contracts cannot be exploited is critical. The goal is to develop a language-agnostic verification approach, following on promising results related to the Solidity