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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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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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Albrecht (Administration) recruiting.leibniz-lsb@tum.de. We look forward to receiving your application! Data Protection Notice: As part of your application for a position at Leibniz-LSB@TUM, you will
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the pyramids and creating digital object models with numerical simulations, for example, using Salvus software or similar. - Publication of research results and presentation of results at scientific conferences
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(Administration) recruiting.leibniz-lsb@tum.de. We look forward to receiving your application! Data Protection Notice: As part of your application for a position at Leibniz-LSB@TUM, you will transmit personal data
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? Our current research is based in India, Rwanda, and Uganda, but we are always seeking ways to learn about and work in new places! You can find out more about us here. About the PhD Researcher Position
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for dynamical systems, causality, and ML for science more broadly. We publish at core ML venues and are also interested in collaborating on applications in biomedicine, climate, or physics. Find out more at
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at Helmholtz Munich together with the Leibniz Institute for Solid State and Materials Research in Dresden developed a new approach for that challenge using surface acoustic wave detection of photoacoustic
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number 2025-15-S2-VS via email to: Anja Albrecht (Administration) recruiting.leibniz-lsb@tum.de. We look forward to receiving your application! Data Protection Notice: As part of your application for a
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, adversarial attacks, and Bayesian neural networks. Excellent analytical, technical, and problem-solving skills Excellent programming skills in Python and PyTorch including fundamental software engineering