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. You have experience with spatial analysis and data processing, preferably ArcGIS or QGIS You have strong interest in linking human behaviour to land-use in the context of biodiversity and ecosystem
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require strong analytical and methodological skills. Candidates will handle data preprocessing and analysis, ideally with proficiency in Python, R, or MATLAB. Collaboration within a multidisciplinary team
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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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University Medical Center Utrecht (UMC Utrecht); Published 31 Oct ’25 | Netherlands | about 1 month ago
validating a machine learning prediction model for CP and related outcomes using neonatal MRI, EEG, GMA, HINE, and clinical data. Coordinating patient inclusion, data collection, and analysis across multiple
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clinical data. Coordinating patient inclusion, data collection, and analysis across multiple NICUs in five European countries. Harmonizing protocols across study centers and engaging with families to gather
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optimization lab (EES EMPDO lab). The former focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and
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) Epidemiology, Bioinformatics or a related field; demonstrated expertise in programming and quantitative data analysis in R/Python; a strong interest in high dimensional omics and exposome research; excellent
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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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. Therefore, dedicated mass spectrometers and LC methods have been and are developed allowing the analysis of the structure and function of protein machineries. More information For more information, please
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volatile geopolitics. Shortages, trade frictions, and financial mismatches can stall otherwise viable tipping dynamics and establish carbon-intensive lock-ins. This PhD will develop an agent-based inspired