58 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" positions at Utrecht University in Netherlands
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of the department at Utrecht University. Where to apply Website https://www.academictransfer.com/en/jobs/357813/phd-position-in-nanoscale-rock-… Requirements Specific Requirements You must have completed an MSc
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brings together expertise on transition management and Science and Technology Studies (STS). The main goal is to further co-develop with the field hands-on methods to support the responsible, societally
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organizational skills. Demonstrable experience with using machine learning packages (e.g., PyTorch). Completed academic courses in AI or machine learning. We consider it an advantage if you bring experience with
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. You will combine technical work on machine learning with qualitative analysis of how AI systems are interpreted and used in organisational decision-making. Join the Human-Centred Computing group
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causal inference, machine learning, text analysis, or large-scale data integration. You support ODISSEI users via consultations and collaborative research, train researchers through workshops, and mentor
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full projects, followed by the analysis, interpretation and reporting of data and results. You will pro-actively promote proteomics services and acquire new collaborative projects. The projects will vary
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and understanding of complex biological systems and biodiversity. You will get the opportunity to learn about both simple and complex biological models, computer programming, data visualisation, and
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, Introduction to Python, making figures using GGplot2 and basic machine learning. These courses are offered to PhD candidates through the PhD Course Centre of the Graduate School of Life Sciences . In
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the ESCALATION study external link on early-onset breast cancer; apply advanced statistical, and machine-learning methods to identify and validate environmental determinants of breast cancer risk; integrate
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering