193 phd-studenship-in-computer-vision-and-machine-learning PhD scholarships in Netherlands
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- Wageningen University & Research; Wageningen
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pharmaceutical companies in expediting and refining the development of next-generation nanomedicines. Information We are seeking an enthusiastic and motivated PhD candidate to join our dynamic team at Nanoworx! As
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percent of your work time, spread over the course of the appointment. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit our website about working as a PhD
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, Industrial Engineering, or related discipline; Affinity and/or experience with computer programming, statistical learning, and optimization techniques; A good team spirit and feel at home at the intersection
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students? This participatory PhD project might be your chance! As a PhD you will be involved in a 4 year NRO (Nederlands Regieorgaan Onderwijsonderzoek) funded project that is contextualised in the Learning
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We’re looking for a motivated PhD student with a
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artificial intelligence, computational cognitive science, human-computer interaction, computer science, information systems, or another relevant field. - A keen interest in pursuing interdisciplinary research
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funded PhD position and you will be offered a course program tailored to your needs and the research team. The gross salary for the first year is € 3059,-. per month rising to € 3881,- in the fourth year
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, conference presentations, and ultimately a PhD dissertation. The PhD thesis is to be completed within four years. You are also requested to teach. You will work with the following supervisory team: - Dr. Frank
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to make viable trading decisions under high price volatility. This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms that are able to cope with
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nature. The PhD candidate will focus on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order