157 assistant-and-professor-and-computer-and-science-and-data PhD positions in Netherlands
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institutes; participate in teaching at the KdVI and assist with the supervision of related research projects for Bachelor and Master students; participate in the Faculty of Science PhD training program
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The successful candidate should have: Master’s degree in Industrial Engineering and Management, Mechanical Engineering, Energy Systems, Control Engineering, Data Science, or a related field, with solid foundations
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firm. Qualifications We’re looking for highly analytical people (math, physics, computer science, statistics, electrical engineering, etc.) who want to help build the research-driven trading firm of
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who has made an outstanding contribution to the humanities or social sciences. The prize consists of a monetary award of EUR 25,000, intended to help finance a research project at the prizewinner’s
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contribution to addressing the major societal challenges of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics
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the selection procedure. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute
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of Science means bringing together inspiring people across disciplines and with a variety of perspectives and backgrounds. The Faculty has six departments: Biology, Pharmaceutical Sciences, Information
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. resilient infrastructure systems 2. value-based project and programme delivery of infrastructure assets. In this project we will closely collaborate with the Tilburg School of Economics and Management
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Employment 1.0 FTE Gross monthly salary € 3,059 - € 3,881 Required background Research University Degree Organizational unit Faculty of Science Application deadline 30 August 2025 Apply now Would
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. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data analysis. For more