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emerging field with your insights. You will learn how to design chemical reaction networks at material interfaces and become a forerunner in chemically-programmable coatings. Briefly, the core objective of
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is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning to apply for the PhD position within
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industrial partners. You are a naturally curious person who is eager to learn more and has a strong interest in research. Excellent written and oral communication skills in English are a prerequisite. We
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hours. Free and unlimited access to our online learning environment GoodHabitz. Pension accrual with the ABP, of which we pay 70% of the premium. A reimbursement of your public transport expenses. Do you
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mitigation strategies. The results will support the development of evidence-based conservation protocols and can provide a learning dataset for AI informed decision that is still lacking in the domain. What we
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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Qualification portfolio. You will be part of the WECARE research team, led by Dr Sonja Marzi (PI). Your supervisors will be Dr Sonja Marzi, Dr Tine Davids and Dr Edwin de Jong. Would you like to learn more about
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for transport You hold, or will shortly acquire, a Master’s degree in a related discipline. Ability and passion for operating at the intersection of different fields, particularly transport engineering and
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to the adaptation of the Environmental Noise Directive for these new technologies. Your main focus will be to develop machine learning-based drone noise models that will be able to generate an accoustic footprint
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skills and a willingness to collaborate within an interdisciplinary research programme. Dutch proficiency (B2), or willingness to learn Dutch, is required due to the fieldwork and Dutch-language sources