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potential new avenues for risk stratification and treatment. Would you like to know more about the different phases within the PhD trajectory? You can read more about this on this page . You will work on a
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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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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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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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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