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Field
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or a PhD in Data Science, Computer Science, or closely related disciplines with industry-relevant research data skills and/or ongoing industry collaboration. Knowledge and expertise in one or more areas
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Scientist to improve the data analysis experience within the MAX IV computing environments. The successful candidate will contribute to developing and supporting the overall software ecosystem for data
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for install across the Network over the next 3 years, replacing mostly Elekta linacs. Cloud-based Aria and Eclipse are presently in process of replacing Mosaiq and Pinnacle. Brianlab ExacTrac with surface
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policies Implement metadata tagging and dataset documentation Oversee on premise and cloud data storage/compute chargeback cost allocations Interface with Fred Hutch Scientific Computing and IT Ensure
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collaborators. These data are stored on a mixture of cloud platforms (e.g., AWS), local high-performance clusters, and protected research environments (e.g., Genomic England). The postholder will work closely
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); containers (Docker/Singularity); CI/CD; build systems (CMake); version control (Git). ● High-Performance Computing schedulers (e.g., Slurm); cloud familiarity. ● Bonus: one or more compiled/scientific
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first class or 2:1 honours) in Computer Science, Software Engineering, or a closely related discipline. A master’s degree or PhD (awarded, recently submitted, or near completion) in a similar discipline
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and informatics research within the School of Public Health (SPH), advancing innovative, multidisciplinary approaches to healthcare and public health challenges. Candidates should possess a strong
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of where time frame may not be clear and where end results may be uncertain. What you bring: PhD in Computational Biology (or statistics with biological applications) Cloud computing experience. Proficiency
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teaching and learning. Desirable Proficiency in technical and digital capabilities relevant to contemporary design practice, including visual communication tools (Adobe Creative Cloud), Computer Aided Design