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Field
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for traceability, robustness, and physicochemical correctness Implement and adapt the most promising algorithms to model radionuclide migration in crystalline host rocks Execute proof‑of‑concept ML simulations and
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supervised deep learning algorithms for 3D laser data from forests Developing self-supervised deep learning algorithms for 3D laser data from forests Expand for a wider variety of downstream tasks focused
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advantages. We will provide the necessary hardware and software for the real-time control of the machine, but the candidate will be responsible for developing and implementing the control algorithms. A working
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contribute to the development of novel algorithms and methodologies that enhance the robustness and accuracy of acoustic measurements. We are looking for a highly motivated candidate, with a relevant MSc
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure, improved mechanical and corrosion properties. Research stays are planned
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university, the internationally accredited registrar and classification society DNV, and Cancer Registry of Norway. You will be analyzing and developing algorithms for privacy preserving health registry data
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learning algorithms, and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen DCs to become the next
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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decision support algorithms in clinical practice. Additionally, the project involves collaborations with large industrial partners such as Roche Diagnostics and SISCAPA. Through this collaboration, you will
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starting date is November 2025. The topic of the PhD project will be theoretical research in discrete optimization, with a particular focus on either graph algorithms or multiobjective optimization