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of an integrated framework. Proficient usage of software development tools (e.g. Github, GitLab) and continuous integration. Basic knowledge of Machine Learning and Machine Learning Operations would be a plus
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(or shortly thereafter). Project background The goal of this project is to leverage advanced machine learning to develop an automated design process of mechanical walking aids, analyse gait patterns and
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characterisation of diagnostic and therapeutic tracers Tumour imaging, clinical oncology and data analysis Semiconductor detectors, nuclear physics and Monte Carlo simulation Machine learning, deep learning and
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characterisation of diagnostic and therapeutic tracers Tumour imaging, clinical oncology and data analysis Semiconductor detectors, nuclear physics and Monte Carlo simulation Machine learning, deep learning and
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mobility. Another research focus is on solid-state pulse modulators for medical applications (computer tomography/cancer treatment) and accelerators (CERN). For the design and optimisation of the various
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(HLS), Intel oneAPI / TBB, ROOT, git, gitlab and continuous integration processes. Basic knowledge of machine learning techniques and tools would be a plus. Strong team collaboration skills and effective
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focuses on psychometric models (e.g., Item Response Theory models), machine learning methods (e.g., Random Forests, Neural Networks, and interpretation techniques), and multilevel models (e.g., analysis
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will be involved in developing a new service for circular information management for construction elements and reality capture in existing buildings using computer vision and machine learning. It
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effective and performant solution for the EF tracking and for EF muon reconstruction and deploy them on the most suitable hardware architecture employing standard numerical and Machine Learning models
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sequences Have experience with computer simulations and programming Your workplace Your workplace We offer ETH offers an exciting opportunity to work at the forefront of scientific research. Collaborations