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programming languages such as Python and experience with deep learning frameworks (e.g., PyTorch, TensorFlow) is highly desirable strong interest in interdisciplinary research combining imaging, machine
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tools for distributed models, and iii) robustness to data and model poisoning attacks. In this context, we are looking for a PhD Candidate who has a strong background in machine/deep learning to push our
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tools for distributed models, and iii) robustness to data and model poisoning attacks. In this context, we are looking for a PhD Candidate who has a strong background in machine/deep learning to push our
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of these materials. Implementation of artificial intelligence (AI) and machine learning (ML) to establish the connection between the existing models and material data (both literature and the baseline established in
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independently and in a team. Drive to learn new methods and applications. Curiosity and creativity in finding problem-related solutions. Contribute actively to a respectful, inclusive and open work atmosphere
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machine learning, distributed systems, and blockchain technologies. Your immediate leader will be the Head of the Cryptology Unit at the Department of Information Security and Communication Technology. The
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mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. Modeling Atomic Processes on Nanoparticles Develop atomistic models and machine-learning
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, and explainable machine learning to analyse campaign text, imagery, and investment outcomes. While experience in analytics or programming is desirable, training and supervision will be provided
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from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques to uncover
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machine-learning methods to enhance predictive capability and enable adaptive process control. Experimental work will include laboratory- and industrial-scale forming trials, supported by comprehensive