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experimental data. Develop computational frameworks for integrating spatial and bulk multi-omics datasets. Create and apply statistical and machine learning models for feature extraction, data harmonisation, and
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for publication and present findings at international conferences Contribute actively to other projects within the research group Requirements PhD in statistics, epidemiology, or a related discipline Experience in
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axes: AI-driven territorial diagnostics and foresight, integrating multi-source satellite data with machine learning and spatial modeling Climate–water–energy–agriculture interactions, with applications
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on complex problems involving the development of new theories and methodologies. The research will be largely focused on the development of predictive computational tools for the analysis of the spatial spread
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Candidate Profile Training and Skills required (Recent) PhD in bioinformatics, statistics, or computer science with knowledge and interest in biology Track record of creativity in developing analytic
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interdisciplinary research teams and internal and external partners. Required qualifications Applicants must have: A PhD in ecology, marine biology, statistics or a related discipline. Strong expertise in statistical
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society are required. Knowledge and skills of GIS and spatial studies are considered advantageous. To apply, please submit your application at https://careers.purdue.edu and include the following materials
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interdisciplinary research teams and internal and external partners. Required qualifications Applicants must have: A PhD in ecology, marine biology, statistics or a related discipline. Strong expertise in statistical
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to Inner-Heliospheric Switchbacks” *(JET2SB, https://anr.fr/Project-ANR-25-CE31-7416 ) project of the French “Agence Nationale pour la Recherche” (ANR) is open for applications to work with the space plasmas
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Website: https://www.systemshematology.org (link is external) How to Submit Application Materials: Please email Asiri (asiri at stanford.edu) Does this position pay above the required minimum