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causal modelling, multilevel methods, difference-in-difference designs) and/or computational methods (e.g., machine learning, mobile-app methods, computational tracking data). You must have an excellent
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reconstructions, integrating reviewed and newly collected data with machine learning techniques. The primary aim is to identify zones of lithospheric fluid generation and the structures facilitating fluid migration
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-services-pons/ ). We are looking for a highly motivated, enthusiastic, empathic person, with passion for research and desire to learn and explore new technologies, aiming at significantly improving her
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-services-pons/ ). We are looking for a highly motivated, enthusiastic, empathic person, with passion for research and desire to learn and explore new technologies, aiming at significantly improving her
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: Machine learning for materials in Energy. Number of positions: 1 Reference: PhD 2025-02 NL Supervisor: Prof. Arjan Kleij / Prof. Carles Bo Project: Computational design of new CO2 fixation processes