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languages, culture, agricultural practices and landscapes of Senegal is an advantage. A driving license. Willingness to learn new analytical and scientific skills. Willingness to communicate and interact with
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. CML distinguishes itself for its attention to professional development in coordination with the interests of its scientists. As such, there are plenty of opportunities to learn new skills, expand your
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of the contract is contingent on sufficient progress in the first year to indicate that a successful completion of the PhD thesis within the contract period is to be expected. The PhD candidate is expected to teach
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adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric
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challenges and to have interactions with stakeholders; excellent English oral and writing skills and willingness to learn Dutch. Our offer A position for one year, with an extension to a total of four years
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learn in situations that are beyond their current capabilities. The ideal candidate has interests in quantitative methods and has a strong motivation for doing health technology assessment/health economic
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observations. Your major challenge is in model development, and there is room for you to develop machine learning applications in the field of firn modelling. If successful, your work will lay the foundation
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. Legal systems worldwide—and particularly within the European Union (EU)—are facing urgent challenges in addressing the ethical and societal impacts of AI-driven applications and machine-learning
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PhD Position: Activating Heritage as a Mediator for Dialogue and Belonging in an Era of Polarization
building in the Netherlands. The Ideal Candidate We are genuinely open and curious to learn how applicants see themselves contributing to this project. We invite you to make a case for how your background
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health behaviour. Using a novel combination of deep learning, street view imagery, and epidemiological methods, we aim to identify the most effective urban exposure modifications. This research will