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About the Role The Research User Computing Linux Specialist designs, operates, and continuously improves KAUST's Linux-based research end-user computing platforms, including Ubuntu and Rocky Linux
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About the Role The Research User Computing Platforms Lead provides hands-on technical leadership for KAUST’s Linux scientific workstation platform, with responsibility for its architecture
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familiarity with machine learning and the ability to work independently and collaboratively. Experience with Linux/HPC environments, machine learning libraries, databases, generative chemistry or drug discovery
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-dimensional genomic datasets. Strong programming skills in Python and/or R, and experience with Linux/HPC computing environments. Experience with single-cell RNA-seq, single-nucleus RNA-seq, sc/snATAC-seq
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service management. Basic knowledge of Linux operating systems. Required Skills Minimum 6 years of experience providing end-user support in a professional IT environment, including: Hands-on experience with
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, biostatistics, computational genomics, longitudinal data analysis, or a related quantitative field; proficiency in R and/or Python and experience working in Unix/Linux computing environments; experience managing
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programming in C/C++, preferably also Rust, and of POSIX, the Linux/Unix kernel or RTOS. Documented competence in parallel and distributed systems, including GPU programming (e.g. CUDA). Ability to explain
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, chemoinformatics and scientific programming is required, alongside familiarity with machine learning and the ability to work independently and collaboratively. Experience with Linux/HPC environments, machine
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C++, Python, and Linux systems to join the Future Mobility Solutions research program. The successful candidate will work on the development, testing, and fine-tuning of self-driving vehicles, ranging
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' bioinformatics experience in functional genomics, multi-omics, comparative genomics or statistical genomics. Demonstrate strong scripting skills using Python, R and Linux-based HPC or cloud environments for large