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-scarce regions. This PhD project will develop next-generation machine learning methods for geospatial prediction by integrating process knowledge into modern AI tools. The research offers the
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€ 3,706 - € 5,760 Deadline 19 Oct 2026 This vacancy is only available in Dutch. Click here to view the vacancy in Dutch. Cookies We use cookies and similar technologies to process your personal data
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the vacancy in Dutch. Cookies We use cookies and similar technologies to process your personal data (e.g. IP address) for personalised content, ads and third-party media integrations. Functional and
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Dutch. Cookies We use cookies and similar technologies to process your personal data (e.g. IP address) for personalised content, ads and third-party media integrations. Functional and strictly
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and your supervisors will determine a plan for a suitable education and supervision. Information and application Selection process: Please submit your online application before 20th August 2026 for
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-place processes and investigate how they improve process efficiency while reducing or eliminating the need for chemical additives. Through this work, you will contribute to the development of next
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phases of the selection process, we will therefore prioritize selecting women who fit the profile. Apply now Hi! Are you my new colleague? Juan Carlos Afonso Hi! Are you my new colleague? Nona Gaies
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, you will investigate and control phase formation, particle size distribution, morphology, and flowability. You will then establish additive manufacturing process windows for these circular powders
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conditions for successful scaling at an early stage of the innovation process. At the moment, there is a need for a better understanding how to approach responsible scaling. In the project you will learn
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, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical infrastructure, and on-campus children's day care. Unlimited access to the