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fields. Design a solution which is implementable on a computer and in hardware. Collaborate with colleagues to implement the solution in hardware at the ACES lab at the Institute of Theoretical
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data • Design clinically meaningful benchmarks and robust evaluations • Publish at leading machine learning and medical AI venues • Collaborate with clinicians, computer scientists, and European partners
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, processing- and product-related aspects as well as nutritional value. Examples are proteins that serve as major nutrients (e.g., cereal storage proteins) as well as those with anti-nutritive activity (e.g
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have
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projects in at least one of the following areas: machine learning, NLP/LLM, data analysis, software development, or medical data processing Willingness to familiarize yourself with medical standards, data
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Regulation (GDPR) regarding the collection and processing of personal data in connection with your application. By submitting your application, you confirm that you have read and understood TUM’s privacy
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criteria into machine-processable representations and safe clinical outputs Implement traceability, uncertainty communication, non-applicability rules and human-oversight mechanisms, and validate system
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biological models. This position involves the optimization, and operation of an innovative multimodal microscope, as well as close collaboration with experts in the biological sciences for its application
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the collection and processing of personal data in the context of your application. By submitting your application, you confirm that you have taken note of the Leibniz-LSB@TUM data protection information