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include: Conducting innovative research and developing proof-of-concept designs, collaborating with sensor providers and other potential collaborators; Writing multiple research articles, collectively
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, posing challenges related to administration, unstable storage conditions, and spatial constraints. Beyond logistical concerns, these collections raise critical questions regarding ownership, colonial
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, creativity, rigor, ownership, and excitement to push research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, data management, and
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mind that proof of a master’s degree is a formal requirement for employment and has to be delivered at least 3 weeks before the start date of the contract. Employment conditions and benefits
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experiments in controlled conditions aiming at simulating natural environments; 3) You will participate in arctic campaigns and use the methods developed to shed light on methane cycling in permafrost regions
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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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phenomena across scales, combining multiple fields including physics, mathematics, astronomy, history & philosophy of science, and social science. Its approach to societal engagement throughout the project’s
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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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. Has experience with qualitative and/or quantitative research methods. Has excellent communicative and project management skills to handle the multiple stakeholders involved in the project (e.g
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analyzing experimental data. Has demonstrable affinity with the topic of sustainable consumer behavior. Has excellent communicative and project management skills to handle the multiple stakeholders involved