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leading role in developing and implementing predictive algorithms designed to identify those most at risk from extreme heat, as well as offering personalized adaptation advice --- translating rich multi
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with evidence of other captures in other fungal species. We seek to understand the evolutionary history and horizontal transfer of the ToxTA transposon in natural populations of all fungal species in
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the group's team-teaching activities. Your profile Applicants should hold an MSc degree in plant sciences, evolutionary biology, environmental science, or related fields. We are looking for a motivated and
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independently by two different Starship transposons, Sanctuary and Horizon with evidence of other captures in other fungal species. We seek to understand the evolutionary history and horizontal transfer
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by combining psychological profiling, biological lab data, physiological time series, and sensor data. The postdoc will play a leading role in developing and implementing predictive algorithms designed
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looking for a skilled Research Engineer to develop and deploy cutting-edge reinforcement learning (RL) and imitation learning (IL) algorithms on real-world robot platforms. The project requires hands
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interested in applied machine learning and computer vision at the intersection of research and industrial deployment. Job description Develop and implement state-of-the-art computer vision algorithms
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develop cutting-edge algorithms and AI-based solutions for data processing and validation and provide scientific expertise for the implementation of future remote sensing missions. The team’s work bridges
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plus. You enjoy working with complex, multimodal datasets and developing robust algorithms for continuous monitoring and predictive modelling. You are comfortable combining coding, data analysis, and
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance