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they learn, PRL134, 147402 (2025). Qualifications We seek candidates with: A PhD in physics, applied mathematics, materials science, mechanical engineering, computer science, or a related field. Strong
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(Faculty of Civil Engineering and Geosciences) and work closely with Dr Louise Nuijens and an (inter)national network of collaborators. QUASI offers a unique opportunity to combine cutting edge observations
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An already acquired Phd in Electrical Engineering, Computer Science, Applied Mathematics, or a relevant field Affinity for formal and simulation models, as well as algorithmic solutions to problems
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your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands. Additional information For more information about
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), and physiological parameters in the study of animal behaviour; a strong background in data analysis using R, preferably experience with Bayesian statistics and social network analysis; lab experience
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Deadline 30 Jun 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a