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Field
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interdisciplinary) research teams Desirable: - very good command of quantitative and qualitative research methods, especially experiences with computational large text data collection and analysis as well as with
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web-GIS development or geospatial data visualization. Experience with high-performance computing clusters or cloud-based Earth observation platforms (e.g., GEE Python API). Experience with airborne
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
30 Jul 2026 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Computer science Mathematics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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. Possible research topics include: Scientific machine learning Numerical partial differential equations (PDEs) Computational fluid dynamics Neural operators High-performance computing Data-driven
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Data Science and Artificial Intelligence (CIDSAI) at NYU Abu Dhabi seeks to recruit a highly motivated Post-Doctoral Associate to work on topics in the theoretical foundations of data science and AI
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Information (QG&QI), Quantum Materials (QMat), and Soft Matter (SM). You will work in the Strontium Quantum Gases Group , part of the QG&QI cluster and headed by Prof. Dr. Florian Schreck. We exploit ultracold
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20 Jun 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Computer science Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1
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investigate the results and implications of the PreFer data challenge – a large data challenge that was held with hundreds of researchers who attempted to predict who would have a child in three years
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but will also include the use of external data for extensive catchment intercomparison. This position is part of a cluster hire with a total of seven positions in Potsdam, Bayreuth, Freiburg and Zürich
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proteins and pathways implicated on disease pathogenesis. We are currently analyzing brain, CSF and blood, multi-omic data (transcriptomics, proteomics and metabolomics), from a large collection of well