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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
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on the basis of the expertise of the candidate as well as the needs of the Department, but will focus on courses of public law both in the bachelor and master’s programs and possibly the Master Law & Technology
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embedded within the group of Dr. Fedor Miloserdov ( Homogeneous Catalysis and Biomimetic Synthesis - WUR ), located in the Laboratory of Organic Chemistry ( Organic Chemistry - WUR ), which is headed by Prof
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, located in the Laboratory of Organic Chemistry (Organic Chemistry - WUR ), which is headed by Prof. Han Zuilhof . You will be supervised by Dr. Laura Righetti and Dr. Gert Salentijn with support by
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machines that will lead to demonstrations with practical relevance. Specifically, this project in the group of prof. Feringa aims to address two key challenges: 1) How can we amplify the work of molecular
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., machine learning, stochastic dynamic programming, simulation). Affinity with (food) supply chain management is preferred. To collaborate with and to co-supervise MSc thesis students and internship students
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PhD thesis within the contract period is to be expected. A PhD training programme is part of the agreement and the successful candidate will be enrolled in the Graduate School of the Faculty
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candidate will be supervised by Prof. Francesco Maresca, chair of the Mechanics of Materials unit of the Engineering and Technology institute Groningen (ENTEG). Organisation Founded in 1614, the University
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the analysis. These logistics concepts must be resilient: robust, adaptive, and flexible. The research questions can be tackled by combining techniques from the domains of Integer programming, (Stochastic