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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
breakthroughs or large-scale adoption events. The module will be validated on both historical datasets and scenario data generated by Integrated Assessment Models (IAMs), large climate-economic models used
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. Your work environment You will carry out this research as part of the ERC-funded RIPPLE project, led by Professor Giacomo Marangoni, and embedded within the Policy Analysis section of the Multi-Actor
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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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large pan-European research initiative that brings together researchers, clinicians, and patient communities. Your project focuses on analyzing multi-omics sequencing data from thousands of patients with
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the vehicle fleet and the multi-objective design of the mixed transporation network. Our key hypothesis is that it is possible to design a mixed network by simulating how to serve a given demand with an
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within FlexMobility will focus on the underlaying assignment and routing algorithms for real-time operation of the vehicle fleet and the multi-objective design of the mixed transporation network. Our key
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for 0.8 fte - 1 fte. The salary starts with € 3.059 gross per month Scale PhD on a fulltime basis (38 hours), in accordance with the CAO-NU. The contract will initially be for a period of one year, with
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University and the Royal Netherlands Institute for Sea Research, you will create ecosystem-specific, mass-produceable structures that are ready for large-scale ecosystem restoration. Your job The PhD candidate
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of materials related to e.g. climate change, modelling and design of railway systems, multi-scale modelling of pavement materials and structures, reuse of materials, structures and parts of structures
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the anaerobic treatment. Hence, a systematic screening of SACs in small scale batch sorption-biodegradation experiments will be combined with continuous expanded granular sludge bed investigations to assess