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related field. Strong track record in remote-sensing imagery and/or time-series analysis and ML/DL for spatio-temporal data. Advanced Python skills and experience with ML frameworks and geospatial tools
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Challenges Addressed in the Position: Heterogeneity and high dimensionality of multi-omics data requiring advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing
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CSAES - Postdoctoral in Experimentation and analysis of the dissolution and diffusion of different fertilizer formulations About UM6P: At the heart of the future Green City of Benguerir
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or defended before start) in Computer Science, Remote-Sensing/Geoinformatics, Agricultural Data Science, or related field. Strong track record in remote-sensing imagery and/or time-series analysis and ML/DL
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, emphasizing your specific interest and motivation Brief research statement. Contact information of 2 referees. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/413705/susmat
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SUSMAT - Postdoctoral Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials About UM6P: Mohammed VI Polytechnic University (UM6P) is an internationally oriented
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advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing values across different omics layers and platforms. Cross-omics data fusion and representation learning
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
23 Jun 2026 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Chemistry Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application
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Position Description: We are seeking a postdoctoral researcher specializing in urban modeling and cost analysis to develop an innovative model to estimate the direct and indirect costs
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage