Associate Computational Scientist Job at Carnegie Mellon University, Pittsburgh, PA

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  • Carnegie Mellon University
  • Pittsburgh, PA

Job Description

Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the curious to deliver work that matters, your journey starts here! The Pittsburgh Supercomputing Center (PSC) — a joint research center of Carnegie Mellon University and the University of Pittsburgh — has been at the forefront of advanced computing since its founding in 1986. For nearly 40 years, PSC has provided university, government, and industry researchers nationwide with access to some of the most powerful systems for high-performance computing (HPC), artificial intelligence / machine learning (AI/ML), high-speed communications, and large-scale data storage for unclassified research. Our work drives discoveries across a wide range of disciplines, including AI/ML, data science, medical imaging, weather modeling, cell biology, and genomics. As an Associate Computational Scientist , you will help researchers unlock breakthroughs by supporting their use of cutting-edge HPC, AI, and data platforms. You’ll work directly with internal and external users to solve problems, answer research and support questions, and provide expert guidance on configurations, best practices, and policies to optimize software performance. You may also develop technical documentation and create training materials to empower our user community. This is an exciting chance to contribute at the leading edge of computational and data science. PSC’s current projects include leading major NIH data initiatives ( HuBMAP : hubmapconsortium.org, SenNet : sennetconsortium.org, BIL : brainimagelibrary.org); national NSF research computing infrastructure ( Bridges-2 : psc.edu/resources/bridges-2, ACCESS : access-ci.org, NAIRR : nsf.gov/cise/national-ai.jsp); innovative AI/ML resources ( Neocortex : psc.edu/resources/neocortex); and specialized supercomputers in collaboration with industry partners ( Anton 3 : psc.edu/resources/anton). Core Responsibilities:

  • Assist research teams with developing, installing, documenting, porting, debugging, and optimizing application-level research software within your scientific domain.
  • Troubleshoot and resolve technical issues referred by the PSC helpdesk, providing timely and effective solutions based on your expertise.
  • Maintain up-to-date knowledge of high-performance computing (HPC), AI/ML, and large-scale data technologies.
Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University. We are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work. Qualifications: • Bachelor’s degree or equivalent, with a strong emphasis in scientific computing. • 1–3 years’ experience in the following areas:
  • Building, installing, maintaining, debugging, and troubleshooting application-level software in UNIX environments.
  • Using shell scripting and batch schedulers such as Slurm.
  • Managing competing priorities across diverse stakeholders, demonstrating excellent interpersonal, oral, and written communication skills.
  • A combination of education and relevant experience from which comparable knowledge is demonstrated may be considered.
Preferred Qualifications:
  • M.Sc. degree.
  • Experience in computational biophysics and molecular dynamics (algorithms and current practice).
  • Experience in AI/ML.
  • Experience in application performance optimization.
  • Familiarity with parallel programming models (e.g., OpenMP, MPI, CUDA).
  • Experience parallelizing serial computational applications.
  • Experience in data analytics.
  • Proficiency with one or more of Python (NumPy/SciPy/Pandas), R, MATLAB, etc.
  • Familiarity with containers such as Singularity, Apptainer, or Docker.
Requirements : • Successful background check Joining the CMU team opens the door to an array of exceptional benefits. Benefits eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits, take well-deserved breaks with ample paid time off and observed holidays, and rest easy with life and accidental death and disability insurance. Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team to help navigate childcare needs, fitness center access, and much more! For a comprehensive overview of the benefits available, explore our Benefits page. At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it’s about finding the perfect fit for your professional growth and personal aspirations. Are you interested in an exciting opportunity with an exceptional organization?! Apply today! Location Pittsburgh, PA Job Function Researchers Position Type Staff – Regular Full Time/Part time Full time Pay Basis Salary More Information:
  • Please visit “Why Carnegie Mellon” to learn more about becoming part of an institution inspiring innovations that change the world.
  • Click here to view a listing of employee benefits
  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
  • Statement of Assurance

Job Tags

Full time, Part time, Work experience placement,

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