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Field
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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 these challenges. By
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We are seeking a highly motivated PhD candidate to join our research team in the field of mixed-signal IC design, focusing on the implementation of sense to compute paradigm. The ideal candidate
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We are seeking a highly motivated PhD candidate to join our research team in the field of mixed-signal IC design, focusing on the implementation of physics-based computing paradigm. The ideal
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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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Do you enjoy working at the interface between behaviour, ecology, and evolution? Then you might be the PhD candidate we are looking for! In this project, you will investigate how swarming behaviour
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The Dutch Institute for Fundamental Energy Research (DIFFER) performs leading fundamental research on materials, processes, and systems for a global sustainable energy infrastructure. We work in close partnership with (inter)national academia and industry. Our user facilities are open to...
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For more information about this position, please contact Prof. Dr. Ilona de Hooge by email: ilona.dehooge@wur.nl . For more information about the procedure you can contact Noorien Abbas, Corporate Recruiter, by email: recruitment.ssg@wur.nl . Ready to apply? You can apply directly using the...
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new models and methods. In this PhD project, you will: develop dynamic supply chain design models that enable the repositioning of AM equipment based on Defence requirements in conflict zones and other
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Delft, and CryoSilico cryo-EM sample supports from DENS solutions to develop a novel reproducible sample preparation method for cryogenic electron microscopy (cryo-EM). You will fabricate microfluidic
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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