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Field
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply
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multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
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Physics , Living Systems , Machine Learning , many-body quantum geometry; altermagnetism; cavity quantum science; quantum non-equilibrium processes; Casimir physics , Material Science , Materials Science
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analysis systems, to ensure safe and trustworthy results. This can involve research questions from NLP and AI like model robustness and guardrails, human-computer interaction such as interpretability and
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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, both written and verbal Knowledge of German and/or a willingness to learn Computer/programming literacy, for example in R, and/or software used in image processing (Adobe Photoshop, ImageJ etc.) Ability
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research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, and natural language processing. Programming skills, e.g. Python, Java
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, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
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to biological data sets such as omics data, protein structure prediction, or biomedical imaging. Technical experience in programming (Python preferred), and/or machine learning is a plus—not a requirement. We