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population genomic analyses of crop species Experience managing and analyzing large-scale biological datasets Experience using SLURM-based high-performance computing systems Demonstrated proficiency in R
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 34 minutes ago
modeling and environmental data analysis, such as Python, MATLAB, Fortran, C/C++, or comparable languages and tools. Ability to work with large datasets and to integrate these data with acoustics models
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develop the urgently needed system understanding, data analysis tools, and forecasting models for science and expert users, and co-create common ground among stakeholders for future-proof coastal management
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a curated catalysis database supporting AI-driven catalyst design. Release data, workflows, and benchmarks via the Materials Project and Genesis AmSC; publish in peer-reviewed journals and present
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from MD Anderson Cancer Center, Rice University and UTHealth School of Biomedical Informatics. Job Duties Analyzes large data sets. Analyzes next generation sequencing data (e.g., RNA-seq, whole genome
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2 Sep 2026 Job Information Organisation/Company University of Liège Department Department of Astrophysics, Geophysics and Oceanography Research Field Geosciences » Other Computer science » Other
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FTE role supporting the international FEVER II study. C-GULL is a large contemporary birth cohort following up to 3-4,000 infants. Nested within C-GULL, HBHF is investigating early predictors of anxiety
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by Professor Tonia Vincent. The successful candidate will contribute to STEpUP OA, a large international Consortium focused on understanding the biological mechanisms underlying osteoarthritis
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At the University of Vienna almost 11,000 personalities work together towards answering the big questions of the future. Around 7,700 of them do research and teaching, around 3,000 work in
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, root imaging) with biogeochemical, microbial, or environmental sensor data. Experience analyzing large datasets in reproducible formats (R, etc.) Demonstrated interdisciplinary and systems-level approach