56 maynooth-university-programmable-city-project PhD positions at University of Groningen in Netherlands
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technology for the forthcoming generation of highly energy-efficient computing systems. FeFETs are programmable, non-volatile silicon devices that enable innovative architectures to efficiently execute complex
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position as a hub for innovation and learning. Located in the vibrant city of Groningen in the northern Netherlands, it attracts talent from across the globe. Located within the University of Groningen
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position is embedded in the research programme Innovation & Organization of FEB’s Research Institute. The project will be supervised by Prof. Ulrike Schultze, Prof. David Langley, and a daily supervisor
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. The PhD position is embedded in the research programme Organizational Behaviour of FEB’s Research Institute. The project will be supervised by Prof. Gerben van der Vegt, Dr Stefan Berger, and Dr Joost van
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The Faculty of Spatial Sciences together with the Faculty of Science and Engineering offer a 4-year M20 (Ubbo Emmius) Program funded PhD position for a project titled “Grassroots retrofitting
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? Organization The PhD position is embedded in the research programme Innovation & Organization of FEB’s Research Institute. The project will be supervised by Prof. Ulrike Schultze, Prof. David Langley, and a
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(Faculty of Law), Christos Emmanouilidis (Faculty of Economics and Business) and Ming Cao (Faculty of Science and Engineering). You will represent the University of Groningen team in project regular meetings
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, Sustainability & Planning’ and ‘Environmental & Infrastructure Planning’, and both bachelor programmes of the Faculty namely ‘Spatial Planning & Design’ and ‘Human Geography & Planning’. Research at the Department
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approaches. The goal is to design an automated reasoning approach in tandem with ongoing formalisation efforts, with a focus on probabilistic behaviours. The objective of the temporary position is the
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unclear strategies for bias mitigation limit its effectiveness in practice. This PhD project addresses the following central research question: how can we design human-AI collaboration to mitigate biases