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flexibility is offered to the grid/market. In this regard, this PhD focuses on optimizing the use of flexibility in electrified process plants by leveraging dynamic behaviors and market participation. With
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learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts. For example, we would like to be able
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asymptotic analysis of stochastic processes Impact: Faster detection of anomalies and reliable uncertainty quantification Job Description As a PhD candidate in Mathematical Statistics, you will develop novel
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interest and motivation to apply for a PhD position in our group, please indicate also when you can start the position at the earliest. An academic transcript of BSc and MSc education, including grades. A
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Are you passionate about understanding the effects of fires on tropical forests? Do you aspire to contribute to cutting-edge research in forest ecology and management? We have two exciting PhD
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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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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 The aim
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theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts
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Description As a PhD candidate in Mathematical Statistics, you will develop novel methods for the analysis of temporal data. Of specific interest are monitoring procedures for structural breaks, which find
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innovative industrial partner in the Brainport region. If all these sounds fascinating, then this PhD position is made for you! Information We invite highly motivated students with a strong background in