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characterizing individual nanoclusters • Engineering and purify protein nanopores with tailored sensitivity to size, charge, and etc. • Developing data analysis pipelines and machine learning approaches for signal
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childhood through adolescence. Data collection will primarily take place in schools, where children and adolescent research participants will complete computer-based learning tasks designed to capture
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applicability. By bridging machine learning, behavioural science, and clinical research, the project seeks to establish foundational methods for trustworthy agentic AI systems that can be deployed across diverse
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cohort of doctoral researchers and benefit from ReDiLEEP training in response diversity methods, data management, reproducible code, R/Tidyverse, machine learning and AI for ecologists, visualisation
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, engineering, and the broader questions of how AI systems affect the people and institutions that interact with them. You should bring: A master’s degree in computer science, machine learning, HCI, or a related
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to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits
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conferences. You can also expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits , and ETH
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, such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ, childcare, and attractive pension benefits. Working, teaching and research at ETH Zurich We value
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and medical innovation Experience with mechanical design, machining, prototyping, or building custom experimental setups is highly desirable Previous experience with focused ultrasound, fMRI
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your professional development, but also actively contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of