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/statistical analyses in one or more of the following programming environments: R, Python, bash, MATLAB, JAVA, etc. 4. Experience using computing clusters (batch processing), cloud computing services, and
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Health Initiative), and local Stanford data. Lab members have access to state-of-the-art computational resources, including cloud-based computing and Stanford high performance clusters. We offer
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position combines MLOps engineering, research software development and technical coordination across cloud, High-Performance Computing (HPC) and federated research environments. A key focus will be the
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data sources. Experience with reproducible research, version control, or high-performance/cloud computing. COMPENSATION AND BENEFITS The hiring range for this position is $61,500 to $64,000. An offer
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using Snakemake, Nextflow, or similar platforms. • HPC or cloud computing environments. • Long-read or single-molecule sequencing, computational epigenomics, and/or 3D genome analysis. • Statistical
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collaboratively in an interdisciplinary team. Good to have Experience in smart contract development, preferably in Solidity. Familiarity with cloud computing and shell script. Knowledge of biomedical
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Postdoc position in Efficient NLP for Information Extraction from News Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application
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Exoplanet Clouds Employer Max-Planck-Institut für Meteorologie Location Hamburg (DE) Salary TVöD E14 Closing date 23 Aug 2026 View more categories View less categories Discipline Computing
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algorithms for analysis of large image datasets. Experience with parallel computing, high-performance computing, distributed computing, and/or cloud-based computational workflows. Experience with large-scale
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management. Experience working comfortably at scale: large and unwieldy data frames, high-performance computing clusters or cloud compute, and workflows that must run reliably on a fixed weekly