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- how do we efficiently identify these growing black holes and measure their properties? This project will focus on that key question, with students learning how to mine the vast new data resource that is
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, engineering, and/or computational approaches to tackle questions at this interface. We are particularly interested in candidates with plans to develop a research program involving mining of large-scale data and
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision
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mathematics. Relevant areas of expertise include data structures, artificial intelligence and machine learning, data mining, databases, data modeling, data ethics, corporate or business analytics, as
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master's degree in: Mining Engineering, Geological Engineering or Geology; The candidate must hold a PhD in Mining Engineering or have developed a doctoral thesis in another area of knowledge, considering
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experimental security (FSec Group: https://vu.nl/en/about-vu/faculties/faculty-of-science/more-about/found… ), with a focus on Cloud computing, the use of data analysis and AI techniques to quantify, evaluate
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science » Computer systems Computer science » Modelling tools Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 May 2026 - 23:00 (Europe/Paris
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more information please contact Prof. dr. Abhishek Garg, mail: abhishek.garg@kuleuven.be or Mr. Nick Geukens, mail: nick.geukens@kuleuven.be . Website for additional job details https://www.kuleuven.be
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22 Jan 2026 Job Information Organisation/Company IMT Mines Alès Research Field Engineering Engineering » Civil engineering Technology » Materials technology Researcher Profile Recognised Researcher
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Engineering, awarded by the Faculty of Engineering and Architecture at Ghent University in Belgium. Further information about this doctoral degree can be found at https://www.ugent.be/ea/en/for-phd-candidates