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knowledge of data analysis and processing, programming, and development of analytical models. Experience with databases and quantitative analysis tools. Ability to work with large datasets and computational
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Institute of Particle Astrophysics and Cosmology (BIPAC), on research aimed at extracting cosmological information from large-scale structure (LSS) and Cosmic Microwave Background (CMB) probes on very large
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5 Sep 2026 Job Information Organisation/Company CNRS Department Laboratoire de Chimie Moléculaire Research Field Chemistry Physics Researcher Profile First Stage Researcher (R1) Application Deadline
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and deep learning methods for large-scale genomic, clinical, and imaging biobank data, with stable multi-year NIH support. The Zhi Laboratory has a sustained track record of methods development
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://aria.org.uk/opportunity-spaces/resilient-climate-and-ecosystems/accelerated-adaptation for more information on ARIA and this programme). The project is a collaboration between groups at the Universities
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implementation of 4D-Var variational data assimilation techniques using observational data, including ROMS 4D-Var or a comparable system. Experience with large-scale HPC workflows, collaborative scientific
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, higher-order network methods and large-scale language-model training on a knowledge graph of scientific publications, patents and related innovation data. The appointed researcher will lead DII's
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Neurodevelopment. You will develop, implement, and apply computational pipelines to analyse large-scale genomic datasets generated through Perturb-seq and other functional genomics approaches. You will use state
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, Python or R Experience in manipulating and analyzing large observation data or model outputs Working knowledge of terrestrial biogeochemistry and nutrient-cycling processes Strong communication skills
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clinical data. A major focus of the position will be identifying genomic and immunologic features associated with variation in immune responses and clinically relevant phenotypes. A Ph.D. or equivalent