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volatile geopolitics. Shortages, trade frictions, and financial mismatches can stall otherwise viable tipping dynamics and establish carbon-intensive lock-ins. This PhD will develop an agent-based inspired
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sciences, economics and regulation. Job description The project of the PhD student based at CWI in Amsterdam will focus on techno-economic models (and in particular multi-agent modeling) of energy exchange
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you like to address this urgent need and develop new methods to support coordinated decision-making for sustainable strategies in the port call? As a PhD student at TU Delft, you will leverage AI (i.e
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, Creating Value-Based Health Care, Functioning, Participation and Rehabilitation, Health Inequities and Societal Participation, Optimizing Patient Care; and Promoting Health and Personalised Care. Working
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-career researcher who is working in and has enduring ties with the Netherlands and who has made an outstanding contribution to the humanities or social sciences. The researcher must have obtained their PhD
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active part in realising their full potential? Do you enjoy working in a team of young and motivated researchers? If so, we have the perfect opportunity for you! Join our team! We are looking for a PhD
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developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative machine learning solutions to optimize
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Published Monday 3 Nov 2025 Deadline Thursday 15 Jan 2026 Work area PhD Organisational unit Rotterdam School of Management (RSM) Salary € 3.059 - € 3.881 Employment 1 fte - 1 fte Abstract Successful
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
. This PhD will develop a machine learning module to detect early warning signals of positive tipping points from techno-economic data, helping policymakers design adaptive strategies for rapid and
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volatile geopolitics. Shortages, trade frictions, and financial mismatches can stall otherwise viable tipping dynamics and establish carbon-intensive lock-ins. This PhD will develop an agent-based inspired