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of Basel. The successful candidate will be part of a cohort of 4 PhD students, 2 research engineers, and 7 principal investigators, working collaboratively across partner institutions. The project will be
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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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schools, where children and adolescent research participants will complete computer-based learning tasks designed to capture metacognitive monitoring and regulation during task performance. The successful
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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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theory, physics-based simulation, and machine learning. Job description The PhD project will develop machine-learning methods for atomistic materials modeling Possible research directions include machine
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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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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position in Toxicology We are looking for a motivated PhD student to join our team
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Infrastructure? No Offer Description PhD position in Modeling and Control of Nonlinear Dynamical Systems from Data The Chair in Nonlinear Dynamics at ETH Zürich is inviting applications for a 100% PhD position in