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About the project and group This position is funded within the context of the “Future Network Services: 6G” project. A unique Dutch alliance, comprising 60 leading ICT businesses, mobile operators
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coordination failures reshape decarbonization pathways. Your research will combine methods from network analysis and agent-based modelling of economic systems to trace how international material and financial
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on these knowledge questions for various clients. Your colleagues, network, existing and new insights, and data will be your allies in this work. In recent years, we have worked on projects that resulted in
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position is part of the network Chair Governance of Complex Urban Transformation that is positioned at the intersection of the Institute for Housing and Urban Development Studies and Team Governance and
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4-year project; regular conditions for a Dutch PhD apply. The position is part of the network Chair Governance of Complex Urban Transformation that is positioned at the intersection of the Institute
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, the ability to analyze complex problems, manage your time effectively, innovate and stay resilient under pressure. Combined with the ability and willingness to work independently and collaborate well
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Positive tipping points in the innovation and diffusion of clean energy technologies can greatly accelerate progress towards a net-zero energy system. Yet, their emergence and timing remain difficult
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climate resilient policies! Job description This 4-year fully funded PhD position is part of the ERC Consolidator project “Systemic physical climate risk in complex adaptive economies” (SPHINX). The SPHINX
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
in the innovation and diffusion of clean energy technologies can greatly accelerate progress towards a net-zero energy system. Yet, their emergence and timing remain difficult to anticipate and manage
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(e.g. safety, norms, networks) influence active lifestyles; develop and test physical activity and destination choice models, integrating data from sources such as sensors, surveys, Google Street View