59 parallel-computing-numerical-methods PhD positions at Technical University of Munich
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, 100% funded PhD student position to fill starting around June 2026. Research is to be in the field of computational methods in nonlinear and large scale optimization / inverse problems or in novel
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University of São Paulo, Brazil. This position focuses on developing advanced computer vision methods and hardware setup for detecting and predicting plant diseases in soybean cultivation. About Us The Chair
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Profile Essential Qualifications Master’s degree (or equivalent) in Mechanical/Civil/Computational Engineering, or related. Strong background in numerical methods in engineering, computational mechanics
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use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry
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systems involved in an effective health care system, rather than creating new medical treatments. Our recent studies have been motivated by two parallel questions: How can we encourage people to engage with
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the application of AI methods in engineering. Description: Nowadays, computer-aided manufacturing (CAM) methods are used to a large extent for the production of complex machine components, in which NC
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information-theoretic approach that embeds security directly into the physical transmission layer, ensuring resilience against future attack methods, e.g., by quantum computers. We are seeking a highly
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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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, leveraging a principled combination of passivity-based control methods, machine learning, and human-in-the-loop systems to enable robust teleoperation in uncertain and delayed communication environments. Key
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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key