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Field
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. Experience with data analysis using language models is beneficial. Experience in the usage and configuration of Linux-based systems. Very good programming skills in Python. Knowledge of another programming
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skills in Git, CI/CD pipelines, and infrastructure automation tools such as ArgoCD, Ansible, Azure DevOps, and Github. Solid foundation in Linux systems, distributed systems and high-performance computing
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demonstrated experience in bioinformatics and/or advanced statistical analyses (e.g. Python/R, Linux environment). Evidence of capacity to problem-solve and troubleshoot independently, with a solutions-focused
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Bioconductor. *Strong foundation in statistics, data analysis, and computational methods; familiarity with machine learning and algorithm development is desirable. *Experience working in Unix/Linux computing
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Research Infrastructure Specialist who can help the CRC (1) support, develop, and manage existing Linux-based core infrastructure that supports centrally managed research environments, and (2) evaluate
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collaborators, contacts, and service providers. Review and address bandwidth and latency requirements. Assist with the configuration and troubleshooting of Linux systems and software that perform data acquisition
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wellbeing. Preferred Qualifications: Working knowledge of Ruby on Rails, PHP, PostgreSQL, AWS, Linux, Git, and JavaScript. React Framework (Front End Expertise). Familiarity with Automated Testing Frameworks
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network, which includes handheld devices, UNIX, Linux, Apple and Microsoft. ● Research the latest product patches and fixes through web access and telephone. Consult with faculty and staff on what computer
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training or fine-tuning large-scale models (LLMs, VLMs) in distributed settings. Familiarity with cluster computing environments (e.g., SLURM) and Linux-based workflows. Prior experience in a research lab
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. * - Other duties may also be assigned. DESIRED QUALIFICATIONS: Proficiency in Python, R, Linux, and command line tools. A strong background in genomics, including WGS, RNA-Seq, and single-cell approaches