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analysis of data and metadata within a big data framework, incorporating bioinformatics analyses, elements of computational biology, and systems biology to extract information from metabolomic data, whole
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 10 days ago
of hybrid modeling frameworks for electromobility, combining physical models, graph-based representations, and data-driven approaches. It aims at integrating large-scale mobility data to improve
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The Role The role focuses on advancing research in explainable and trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data
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well as secondary data wrangling and analyses on large, cross-national datasets from dozens of countries across 4 waves on adolescent identity, school experiences, and social outcomes. This role will also entail
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, Division of Computational Biology) on research using large-scale EHR data sources, including Epic Cosmos and PEDSnet. Ideal candidates will have experience in one or more of the following areas: EHR-based
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. The project enables a targeted combination of expertise from machine learning, data science, and education with insights from educational practice. Drawing on large-scale data from authentic educational
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and/or slitless spectroscopy datasets and/or JWST imaging datasets Development of methods for large spectroscopic surveys and data products This is a two-year term appointment from date of hire with
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, or real-time data processing for large experimental datasets. Familiarity with multimodal data integration and scientific data management frameworks. Interest in the development of AI-guided or autonomous
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13 Apr 2026 Job Information Organisation/Company Max Planck Institute for the Physics of Complex Systems Research Field Physics » Biophysics Physics » Thermodynamics Physics » Statistical physics
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classification. • Perform image preprocessing, annotation, and quantitative feature extraction using clinical datasets. • Manage and organize large-scale imaging datasets with attention to data quality, de