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of Design will contribute with two PhD students to establishing EPIs by developing and using innovative design methods to extend the space of imaginable policy pathways. This vacancy concerns one of these two
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methods to be considered for numerical optimization by an Energy and Emission Management System (EEMS). Data-driven AI methods (e.g. Reinforcement Learning and/or Recurrent Neural Networks) to be considered
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methods is expected. Digitizing Sexual Violence takes as a starting point that new technologies, such as smart phones and social media platforms, have become vital to social connections; moreover, they have
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starting the PhD). The candidate must be qualified for admission to the ph.d. program Strong background in quantitative methods (reflected in courses and/or research experience) Proficiency in R, Python
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immediate leader will be associate Professor Victorien Prot. About the project This PhD position aims to increase our understanding of the mechanics of heart valve diseases using cutting-edge computational
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packages B/G: Current Policy Pathways & Redefining the Policy Landscape • Work packages C/H: Socio-Political Contexts and Effects We are looking for a candidate with strong quantitative methods skills
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, enabling multi-vessel charging and scalable maritime electrification. Advanced control strategies and data-driven optimization methods will be considered to enhance the efficiency, sustainability, and
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requirements Will be considered as positive experience from relevant research projects experience with genetic epidemiology methods experience from international collaboration The applicant’s personal
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as positive experience from relevant research projects experience with genetic epidemiology methods experience from international collaboration The applicant’s personal suitability for the position is