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19 Sep 2026 Job Information Organisation/Company CNRS Department Centre de Recherche en Informatique, Signal et Automatique de Lille Research Field Engineering Computer science Mathematics
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spectra of other stars and, hence, to investigate the solar-stellar connection for the corona. The project involves the analysis of archival solar imaging and spectroscopic X-ray data. The project will be
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to the activities of the Machine Learning & Data Science research group, develop rigorous mathematical proofs for convergence and asymptotic analysis of deep learning models, methods and algorithms, and collaborate
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framework for the joint analysis of large-scale structure (LSS) and gamma-ray data. By combining these complementary probes of the same underlying matter distribution, the project aims to sharpen constraints
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-Chem simulations for modeling aerosols and clouds in the Arctic region. - Analysis of the interactions between aerosols, clouds, and climate using data from the simulations. - Validation of the models
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analysis. Our laboratory develops physiologically relevant in vitro platforms, including three-dimensional culture systems, tunable hydrogel matrices, microfluidic devices, organ-on-chip models, and
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of bacterial genomes and comparative genomics across different strains. * Bioinformatic analysis of genomic data and identification of genetic variants associated with the observed phenotypes. * Integration
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InLife Institute of Animal Reproduction and Food Research, Polish Academy of Sciences | Poland | 11 days ago
, and identification of c-sncRNAs associated with egg and sperm quality. Position description: The successful candidate will participate in molecular research, data analysis, and interpretation of results
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factors assessment). You should hold a relevant PhD/DPhil (or near completion) and have publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a
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will lead and participate in observations and data analysis across the electromagnetic spectrum, or will lead work on machine learning classification of optical transients. Applicants with previous