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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cmptl and Data Sci Rsch Spec 3 - 141146 - **Company:** University of California, San Diego - **Location:** San Diego, CA, United States - **Contract:** Permanent contract - **Skills:** Microsoft Access, Artificial Intelligence, Algorithm Design, Data Analysis, Application Testing, Profiling, Computer Programming, Software Debugging, Microprocessors, File Systems, Distributed Systems, Ethernet, Field-Programmable Gate Array (FPGA), General-Purpose Computing on Graphics Processing Units, InfiniBand, Machine Learning, Azure Machine Learning, Scientific Computating, Ceph (Software), Graphics Processing Unit (GPU), High Performance Computing, Jupyter, Kubernetes, Information Technology, Machine Learning Operations - **Published:** August 29, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18127376?backUrl=%2Fcareer%2F18127376%2FCmptl-Data-Sci-Rsch-Spec-3-141146-California-San-Diego ## About the Role * Bachelor's degree in related area and / or equivalent experience /training. Master's degree preferred. * Advanced skills and demonstrated experience associated with one or more of the following: HPC hardware and software power and performance analysis and research, design, modification, Implementation and deployment of HPC or data science or CI applications and tools. * Thorough experience working in a complex computing / data / CI environment encompassing all or some of the following: HPC, data science infrastructure and tools / software, and diverse domain science application base. * Demonstrated broad experience in one or more of the following: optimizing, benchmarking, HPC performance and power modeling, analyzing hardware, software, and applications for HPC / data / CI. * Demonstrated experience in using AI/machine learning approaches in domain science applications. * Proven ability to work in a Kubernetes cluster environment with experience using it for either research or education. SPECIAL CONDITIONS * Job offer is contingent upon satisfactory clearance based on Background Check results. Pay Transparency Act Annual Full Pay Range: Unclassified - No data available (will be prorated if the appointment percentage is less than 100%) Hourly Equivalent: Unclassified - No data available Factors in determining the appropriate compensation for a role include experience, skills, knowledge, abilities, education, licensure and certifications, and other business and organizational needs. The Hiring Pay Scale referenced in the job posting is the budgeted salary or hourly range that the University reasonably expects to pay for this position. The Annual Full Pay Range may be broader than what the University anticipates to pay for this position, based on internal equity, budget, and collective bargaining agreements (when applicable). ## Description The Data Enabled Scientific Computing (DESC) division within SDSC designs and jointly proposes with other SDSC researchers, supercomputing systems in response to tens of millions of dollars call-for-proposals from the National Science Foundation (NSF), various government organizations and UC entities; it responds to calls for proposals for cyberinfrastructure (CI) related research, solutions and support. DESC manages, operates and troubleshoots issues with advanced, leading edge, complex, multi-petaflop and multi-petabyte data intensive supercomputer systems, file systems (Lustre, Ceph, BeeGFS etc.), interconnects (such as InfiniBand, NVLink, Slingshot, ethernet etc.) and CI projects housed at SDSC. Research leaders within DESC submit high performance computing (HPC), high throughput computing (HTC), Artificial Intelligence (AI), CI, data science, computational science, science gateways and scientific software research proposals and acquire funding from NSF, National Institutes of Health (NIH), Department of Energy (DOE), Department of Defense (DOD) and industry. DESC carries out supercomputing, AI, CI, data science, computational science and scientific software research and development projects. This division provides consulting and user support at the national level, at UCSD and UC-wide to researchers and users from academia at various US universities and institutions as well as collaborates with them and industrial users. DESC provides advanced computational science, AI, CI and scientific software support for the national and UC user communities as a part of projects/machines such as the Expanse machine (a six-year ~$38-million project funded by the NSF and enables tens of thousands of users to use HPC, HTC and GPUs), the Voyager machine (a five-year, ~$12-million project funded by the NSF and enables researchers to experiment with and use AI-focused hardware for scientific applications), the PNRP project ( a five-year , ~$12-million project funded by the NSF and enables distributed computing with resources of GPUs, FPGAs and CPUs), Cosmos machine (a five-year ~$12-million project funded by the NSF and democratizes access to accelerated computing), the Expanse2 machine ( currently a two-year $10-million project funded by NSF and will be extended for a total of five-years with additional ~$12-million to enable tens of thousands of users to use HPC, HTC and GPUs), the CloudBank2.0 project ( a five-year, ~$37-million project funded by the NSF to enable usage of commercial cloud resources by academic researchers) and the Triton Shared Compute Cluster (TSCC - which is a UCSD condo cluster for UCSD and external researchers and provides the NIST 800 171 compliant HPC and GPU computing). Various other funded CI research and development, and domain science (e.g. biochemistry, bioinformatics, cosmology, physics, engineering etc.) and AI/ML projects are directed by DESC researchers. DESC staff and researchers are involved with and funded by the NSF funded Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program that coordinates various user support, allocations, and training related activities and operations at a national scale across all the NSF funded supercomputer centers located at multiple universities. DESC staff and researchers are involved with and funded by the NSF funded National AI Research Resource (NAIRR) Pilot project which is a multi-institutional national scale project that aims to connect U.S. researchers and educators to computational, data, and training resources needed to advance AI research and research that employs AI. DESC researchers are Co-PIs, subaward site PIs on national scale multi-organization centers and institutes funded by federal funding agencies such as NSF and DOE at the scale of tens of millions of dollars. DESC researchers and staff are involved as PIs, Co-PIs and Senior Personnel in various HPC/HTC/AI training, workshop, outreach, workforce development and K-12 student programs and associated NSF funded projects at the level of multi-million dollars. DESC researchers set trends on R&D and CI/AI training directions involving combination of HPC, HTC, accelerators, AI, CI, scientific software, and domain sciences. This division stays current with HPC, HTC, accelerators, AI, CI, computational science and scientific software research and technology trends. DESC staff engage with supercomputer vendors (e.g. Dell, Supermicro, Intel, NVIDIA, AMD, IBM, Hewlett Packard Enterprise, Data Direct Network, Aeon Computing, Arista, Cambridge Computing etc.) to remain current with future technologies utilized in supercomputer designs. POSITION OVERVIEW: The Computational and Data Science Research Specialist (CDSR) applies skills as a seasoned, experienced IT research professional and uses computational, computer science, data science, and CI software research and development principles, with relevant domain science knowledge where applicable, along with professional programming concepts for medium-sized projects or portions of larger projects. The incumbent develops and optimizes a variety of computational, data science, and CI research tools and components; performs research on current and future HPC, data, and CI technologies, hardware and software projects; and works on algorithm development, optimization, programming, performance analysis and / or benchmarking assignments of moderate scope where the tasks involve knowledge of either domain / computer science research requirements and / or CI design / implementation requirements. As a computational & data science researcher, provides advanced application and user support for SDSC's cutting-edge HPC and AI resources, including the Prototype National Research Platform (PNRP), Expanse, Voyager, and Cosmos. The position involves porting research workflows to these innovative resources, developing operational procedures and tools for reliable usage, and integrating these resources into the production research infrastructure. The incumbent creates documentation and tutorials to support the broader use of advanced HPC hardware, such as FPGAs and high-end accelerators, and assist user support staff in onboarding new users. Additionally, provides advanced support for complex issues related to writing, developing, debugging, profiling, and running applications on Kubernetes clusters with novel resources like FPGAs and Habana Gaudi processors. This includes conducting in-depth analysis of factors impacting user code performance and performing complex troubleshooting in a Kubernetes environment. The CDSR supports the use of machine learning tools on SDSC resources for a diverse research community and advise on software and algorithm choices for data-intensive problems. The incumbent also collaborates with the systems group to integrate advanced HPC hardware, including FPGAs and high-end accelerators, into the PNRP and Voyager clusters, modifying software stacks to enable network and scientific applications to utilize these innovative resources. This includes developing, testing, and implementing software stack modifications in the production environment for user access. In addition, develop and maintain comprehensive documentation and tutorials on FPGA and innovative hardware/software resources available at SDSC, keeping usage documentation updated, and presenting tutorials to enable broader use and assist user support staff in onboarding new users. Provides user support to help researchers and educators integrate SDSC and NRP provided inference services into their workflows and classes, including use within Jupyter environments. Responsibilities will also include developing and maintaining benchmark suites to test FPGAs and innovative hardware on SDSC Kubernetes clusters, providing advanced support for testing, implementing, and integrating complex domain science applications into workflows on Kubernetes-based clusters using innovative hardware/software components. The incumbent works closely with SDSC research staff to aid and participate in proposals utilizing SDSC's unique HPC resources, such as Expanse, Voyager, PNRP, and Cosmos, as well as in proposals for future CI resource procurements. This involves running applications and micro-benchmarks to characterize performance in support of proposals, designing and implementing plans to use application test cases to highlight the unique features of proposed systems, including computational features, virtualization, high-performance networks, and I/O components. 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