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Field
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Infrastructure? No Offer Description The PhD candidate will work on the development of advanced statistical and machine learning methods for time series prediction, with applications mainly in the field of traffic
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three-year PhD–positions related to use of AI for mapping of forest ecosystems. New sensors and increased digitalization generate vast quantities of data that together with advanced statistical methods
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PhD Opportunity: Critical transitions in timeseries from soil & earthquakes From the collapse of the Amazon rainforest to financial markets, from earthquakes to degraded farmland - complex systems
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4th May 2026 Languages English English English Want to help build a Digital Twin for wood façades: from microclimate exposure to degradation risk? PhD within Microscale weathering and performance
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at understanding the interplay between the above physical effects on the microstructure evolution of Al alloys during additive manufacturing using the phase-field method. The PhD student will use an in-house phase
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statistics This PhD project falls under the collaboration between Research Thrust RT2 Physics-based models, and Research Thrust RT3 on representation, compression, learning, and inference. For long-distance
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Project summary: How does exposure to electricity price risk shape the way investors value European companies? Using textual analysis and financial econometrics, this PhD will construct new
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knowledge of statistical analysis (e.g., R or equivalent) Openness and motivation to apply for a student grant or external funding during the PhD Additional advantages (not required but welcome): Experience
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Project description This PhD position is embedded in the NWO Vidi–funded research
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Ecoscience programme. The position is available from 01