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, atmospheric forcing, and human activities. Measuring and modelling this complex ecosystem is particularly challenging because of its high spatial and temporal variability, which requires dedicated and adaptive
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temporal scales from seconds to hours and beyond. The aim of this PhD project is to build a multi-scale model linking molecular renewal to functional properties of synapses to study the relationship between
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS), developed by NASA’s Global Modeling and Assimilation Office
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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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) Positions PhD Positions Application Deadline 11 Feb 2026 - 12:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 2 Mar 2026 Is the job
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in person in São Paulo and involves single-cell and spatial transcriptomics analysis, integration of multi-disease datasets, investigation of cell–cell communication, and the development
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Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 days ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Candidate (f/m/x) - AI/ML Drug Discovery for Brain
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. Parametric algorithms and ML models trained on simulation-derived and measured datasets will approximate key microclimate variables and associated human–bioclimatic responses across a wide range of spatial and
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, numerical implementation, and analysis of multi-scale heat transfer phenomena. Co-supervise PhD students and contribute to mentoring early-career researchers involved in related modelling activities. Attend