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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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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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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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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
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optical simulation skills (Preferably in Zemax) Strong programming skills (preferably in Python) Experience in deep learning algorithms is a plus Ability to work in a highly international team and
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flow reconstruction, enabling both real-time coarse diagnostics and high-fidelity offline velocity field estimation. Developing reinforcement learning (RL) algorithms for a multi-agent robotics system
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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi