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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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meals for field teams, and renting and driving vehicles. Collecting and processing data, and ensuring regular backups to RUG and KNIR storage systems. Short stays at the KNIR Institute in Rome may be
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Master’s degree in Data Science, Artificial Intelligence, Computational Linguistics, Computer Science. Has excellent academic writing and oral skills in English. Has experience with large language models
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the project, primary data collection will need to be done in Southern Kenya (Narok and Kajiado counties). Maasai Mara University in Narok county will provide on-the-ground assistance. The PhD position is
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will also carry out this mission in the outside world through teaching, delivering lectures, providing information, and participating in public debates. If you wish, you can combine this position with
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groups in particular to apply. For more information, see also our diversity policy webpage: https://www.rug.nl/about-ug/policy-and-strategy/diversity-and-inclusion/ Our selection procedure follows
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format (e.g. a practice-based piece with a reflective text). Contact information of two academic referees: Please provide the full names, institutional affiliations (if applicable), and email addresses
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. For more information, see also our diversity policy webpage: https://www.rug.nl/about-ug/policy-and-strategy/diversity-and-inclusion/ Our selection procedure follows the guidelines of the Recruitment code
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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping