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systems. Assist research groups with migrating or scaling workloads to CARC’s HPC systems or cloud platforms when local resources are insufficient. May be responsible for administration and oversight
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can be found on the PI’s website: https://aobol.github.io/AoboLi/ The position builds on the group’s recent development of SIDERIUS, an agentic framework for long-horizon machine-learning development
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scripting skills in Python, R, and Bash Comfort working on the command line, including in a Unix/Linux environment Familiarity with high-performance computing (HPC) and high-throughput computing (HTC
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Institute of Science and Technology Austria (ISTA) | Klosterneuburg, Niederösterreich | Austria | about 2 months ago
analysis equipment and services Take part in establishing and maintaining data-infrastructures, repositories, Research Data Management (+large-data handling) and HPC cluster computing (in collaboration
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, probabilistic modeling, and learning from noisy or incomplete data is a plus Practical experience with High Performance Computing (HPC) systems is an advantage Your experience should be documented
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individuals to hundreds of thousands. These will be executed at scale via distributed software solutions on both local HPC and cloud-based assets. Our datasets comprise petabytes, and are growing rapidly
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control, and audit trails across HPC, local servers, tape, and cloud platforms. Cloud & Archival Storage: Administer tape- and cloud-based storage environments (AWS S3, Dropbox, Box, institutional
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omics data. • Knowledge of environmental or molecular epidemiology. • Experience with machine learning or multimodal data integration. • Experience with high-performance computing (HPC) cluster systems
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ambitious as well as being welcoming and supportive. The applicant should have high proficiency with scientific computer programming in Python, Julia, R and/or MATLAB, parameter estimation methods and HPC
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working on the command line, including in a Unix/Linux environment Familiarity with high-performance computing (HPC) and high-throughput computing (HTC) environments and job schedulers such as SLURM and