UCSD Layoff from Career Appointment: Apply by 4/11/23 for consideration with preference for rehire. All layoff applicants should contact their Employment Advisor.
Special Selection Applicants: Apply by 4/21/23. Eligible Special Selection clients should contact their Disability Counselor for assistance.
Job posting will remain open until a suitable candidate has been identified.
DESCRIPTION
DEPARTMENT OVERVEIEW:
The San Diego Supercomputer Center (SDSC) is a world leader in using, innovating and providing cyberinfrastructure to enable advances and new discoveries in science and engineering. Focusing on data-oriented and computational science and engineering applications, SDSC serves as an international resource for data cyberinfrastructure through the provision of software, hardware and human resources in multidisciplinary science and engineering, and is a leading national cyberinfrastructure center to the National Science Foundation (NSF) and broader community.
The Scientific Computing Applications group at SDSC focuses on developing, optimizing, parallelizing, porting, benchmarking and supporting software, including domain science software in bioinformatics, phylogenetics, astrophysics, math libraries etc., that run on High Performance Computing, High Throughput Computing and cloud resources as well as development of cyberinfrastructure software related to science gateways. When applicable, emphasis is placed on making the most effective use of the unique systems located at SDSC. These currently include Expanse, enabling long tail of science for the majority of computational researchers who require small-to-medium numbers of compute nodes for their jobs, Voyager, an AI-focused supercomputer for deep learning applications from broad areas of science and engineering, and National Research Platform (NRP) which has GPU resources, FPGAs and a nationally distributed data and compute infrastructure. The Scientific Computing Applications Group also studies the feasibility of new technologies and provides input regarding the selection of new resources.
POSITION OVERVIEW:
The incumbent's primary role is to work in long-term collaborations supporting the work of Domain Scientists using the SDSC systems focused on High Performance Computing (Expanse) and GPU/Deep Learning (Voyager and National Resource Platform HPC Subsystem).
The incumbent should have a background as a computational scientist in any scientific domain and know how to leverage that experience to interface with scientists in other disciplines to jointly bring a research project to fruition. Under the direction of the "Scientific Computing Applications" lead, this position exercises independent judgment in developing methods, techniques, guidelines and evaluation criteria for obtaining results on project activities, milestones, and deliverables, showing in depth ability to successfully work on concurrent projects and advanced skills in independently resolving complex computing and data problems.
Additionally, they will independently design, implement, debug, benchmark and/or profile software projects in the domain of High Performance Computing, High Throughput Computing or Cloud Computing, relying on knowledge of multiple areas within: Parallel programming (MPI / OpenMP) in Python, C++ or FORTRAN, debugging and benchmarking of parallel software, SLURM, Software development best practices (Version control, Continuous Integration, Packaging, Writing documentation), Deep learning, Docker or Singularity Containers, Cloud Computing (creating Virtual Machines on AWS, Google Cloud or similar), Kubernetes, GPU programming with CUDA, data processing, metadata handling, optimization of disk access.
Bachelor's degree in computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience required. Master's degree preferred.
Intermediate knowledge of HPC / data science / CI. Demonstrated previous experience with Deep Learning frameworks like PyTorch or Tensorflow.
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. Advanced knowledge of modern software engineering techniques, including version control, documentation, testing, design, requirements gathering and deployment.
Demonstrated knowledge of multiple topics within: Parallel programming (MPI / Op
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