Research Computing Services (RCS) at Boston University has one immediate opening for a well qualified candidate to join our group and support BU’s research computing community.
For over 35 years RCS has provided consulting, training, and infrastructure support to thousands of researchers on the Charles River and Medical Campuses. RCS supports a wide range of disciplines from the Physical Sciences and Engineering to emerging computational communities such as Biostatistics, Bioinformatics, Genomics, Neuroscience, Machine Learning, Public and Global Health, Economics, Finance, Social Sciences, Microbiology, and Infectious Diseases. RCS manages the University’s Shared Computing Cluster (SCC) a Linux cluster with over 18,000 CPU cores, 300 GPUs, and 6.5 PB of disk for research data. RCS serves over 2,400 researchers in over 720 projects from more than 80 departments and centers at the University. Additionally, RCS manages much of the Northeast ATLAS Tier 2 center facilities including 5,500 CPU cores and 4.7 PB of storage. The ATLAS cluster serves more than 3,000 researchers world-wide.
Boston University is a founding member of the Massachusetts Green High-Performance Computing Center (MGHPCC) along with Harvard, MIT, Northeastern and the University of Massachusetts. The MGHPCC is a research computing data center which includes 33,000 square feet of computer room space optimized for high performance computing systems, a 19MW power feed, and a high efficiency cooling plant that can support up to 10MW of computing load.
The Research Computing group actively participates in intra- and inter-university collaborations, both regionally and nationally, including participation in the XSEDE Campus Champions program and the Northeast CyberTeam program.
RCS is a major partner in the Massachusetts Open Cloud (MOC), an initiative to build an open alternative to today’s public clouds, as well as the Commonwealth Cloud for Computational Biology (C3DDB), a project which supports research connecting life science with big data analytics. Both of these projects are funded by the Commonwealth of Massachusetts and are collaborations with our partners at the MGHPCC.
Boston University is one of the leading private research and teaching institutions in the world, and one of the largest employers in the city of Boston. With over 35,000 undergraduate and graduate students from more than 130 countries, 10,000 faculty and staff, 17 schools and colleges, and 300 programs of study, our three campuses lead the way in world-class education and innovative research. BU has a rich legacy of serving both greater Boston and the world community.
Boston University’s policies provide for equal opportunity and affirmative action in employment and admission to all programs of the University.
For more information about the Research Computing Services group please visit rcs.bu.edu.
To apply for the open positions, please visit www.bu.edu/hr/jobs/how-to-apply/
As a member of the Research Computing Applications team engage researchers as partners to co-create and co-learn research activities and relevant advanced computing capabilities to provide solutions to facilitate and transform research. Work directly with faculty, staff, and graduate students on complex projects that require in-depth knowledge of scalable parallel programming (MPI, OpenMP, SIMD, GPU) supporting efficient utilization of Boston University’s HPC resources. Provide support for the application of container technology and use of regional and national resources to research workflows. Install, document, and validate existing researcher facing software packages. Provide outreach and training to the university research community. Collaborate with regional and national research computing peers on the fields landscape and best practices.
- Minimum of Master’s Degree in relevant post-secondary education and 3 years of relevant work experience or Doctorate Degree and 1 year of relevant work experience.
- Minimum of 3 years experience and in-depth knowledge of programming in parallel environments (e.g. MPI, OpenMP, and CUDA or OpenCL).
- Demonstrated proficiency in multiple programming languages, particularly C, C++, MATLAB, Python and strong competencies in algorithms and numerical analysis.
- Ability to quickly learn new programming languages and tools.
- Proficiency with parallel/distributed computing on HPC systems (experience with National SuperComputing centers a plus).
- Fluency in Linux scripting and software package installation.
- Strong analytical and personal skills with an ability to manage multiple projects and deliverables, strong attention to detail.
- Excellent organizational and communication skills, and the ability to work well both independently as well as in a team.