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fulltime position and only internal staff members of the University of Groningen can apply. Life-long learning has become crucial in education, work and in society due to compelling social, economic and
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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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: 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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, and susceptibility to interference. The objective of this 4-year PhD position is the production of a number of research articles in peer-reviewed scientific journals and conference proceedings, which
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that needs to be fulfilled to be selected for an interview. For the other criteria, we expect the candidate to fulfill the majority of these criteria. Additional Information Benefits The chair is a position at
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; optimisation, systems and control; and sustainable chemical engineering and biotechnology. Qualifications The ideal PhD candidate for this position is a talented engineer with a Master's degree and has
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(e.g. municipality of Groningen and Emmen), etc. This PhD project is one of two positions available within FEBRI that are part of S3ORTED and focus on the business side of this mission. Within
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://www.rug.nl/education/phd-programmes/prospective/phd-positions/english-language-requirements?lang=en ). The ideal candidate will also have: Data wrangling experience in extracting data from databases (e.g
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. Your PhD thesis and/or an academic paper. You may apply for this position until 10 September 11:59pm / before 11 September 2025 Dutch local time (CEST) by means of the application form (click on "Apply
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We are looking for a talented and enthusiastic candidate for a fully funded 4-year PhD position. The PhD candidate for this project will be working at the RNA Structural Ensemble Dynamics group led