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Field
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geoscientific applications. Current research includes large-scale crop mapping, wetland monitoring, and the integration of machine learning with remote sensing and geophysical data for groundwater mapping. Your
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surface-chemistry trends across selected metals and their oxides. These data will support the construction of a machine-learning force field tailored to NHC–surface systems, enabling large-scale molecular
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Laszlo Bakó (molecular biology) and Torgeir R. Hvidsten (comparative genomics). The environment provides comprehensive support for large‑scale multi‑omic data generation/analysis and transformation
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within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning in the Natural Sciences
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analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division, Computing and Computational
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continue to be reviewed until August 31, 2026 or until the position is filled. This position is for a post-PhD trainee preparing for a research scientist career path. The planned position will provide a
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Biology is looking for a highly motivated and independent individual to work as a Postdoctoral Associate. This position is for a post-PhD trainee preparing for a research scientist career path. The planned
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Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | 2 months ago
Studies (CAS ) at the MPE invites applications for an Astrochemistry Postdoctoral on computational chemistry. A particular focus of the project is on utilizing machine learning techniques for molecular
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell