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, transformer-based models), including experience with their application to biomedical and biological data; Experience with machine learning frameworks and programming languages (e.g. Python) for handling large
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; Distributed multi-agent sensing and cooperative positioning algorithms; Machine learning and data-driven methods for ambient awareness. Working Environment: The PhD will be conducted at the University
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, volcanology, critical raw materials, and machine learning / AI. The network combines advanced petrological observations and multimodal analytical data with modern ML (including physics-informed and generative
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(Python or C/C++) with experience in systems engineering and software development. Solid knowledge of both basic and modern methods in machine learning, NLP and computer vision, including supervised and
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. ESSENTIAL REQUIREMENTS A PhD inMachine Learning, Computer Vision, Computer Science, Physics, Engineering, Mathematics or related areas. Documented expertise in: Machine/Deep Learning, and possibly Computer
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dependable large-scale software systems, integrating expertise in: Software Engineering Machine Learning & MLOps Robotics & Cyber-Physical Systems Cloud & HPC ecosystems Interdisciplinary research. As a
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artificial intelligence (AI) and big data mining methods for real-time defect detection and adaptive process optimization in Electron Beam Powder Bed Fusion (EB-PBF) of refractory metals such as tungsten and
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Responsibilities Conduct foundational research in adversarial machine learning, exploring novel attack vectors and defense mechanisms for AI agents and large language models. Develop formal verification methods and