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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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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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Plan programme, aimed as a flagship project for changing planning and scheduling in high mix low volume (HMLV) production by leveraging hybrid AI, data-driven workload estimation, intelligent release
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on food safety. The researcher will be responsible for planning and conducting field sampling and laboratory assays, including the development and validation of multiresidue methods by liquid chromatography
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-driven workload estimation, intelligent release planning, and explainable decision support. The PhD will operate across two worlds: The University of Twente — advancing scientific models, algorithms, and
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both methods by applying the formula defined above in IV.7. V.2.4. The notification of the draft’s final decision to the candidates, which contains the list with the proposed ordering of the successful
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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classification Estimation of the probability of developing diseases Anomaly detection Early diagnosis. The recipient will learn and apply a vast portfolio of complementary and synergic methods at the intersection
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes