Computational Scientist- HPC/AI Generalist

RCC also helps researchers leverage local, national, and cloud-based computational resources. The Office of Research oversees sponsored research administration, research development, and contract management across the University. Job Summary The job develops software to support the data acquisition, ingestion, and integration for research projects. Assists in the development of user interfaces and scalable back-end services to automate and accelerate the scientific output of multi-institutional research projects. The Research Computing Center (RCC) is seeking a highly motivated Computational Scientist to work closely with faculty and researchers at The University of Chicago. The person in this position will serve as a multi-disciplinary technical expert in supporting and advising faculty on using High-Performance Computing (HPC), AI, and related technologies for their research. The successful candidate will join a team of Computational Scientists who are playing a key role in scientific computing support at the University of Chicago. This is a hybrid position requiring 3 days onsite. Responsibilities Partner with faculty and research groups as a domain expert to develop and implement computational solutions that advance their research. Advise on the effective use of RCC resources, HPC systems, AI technologies, and cloud platforms. Support researchers' use of AI and machine learning tools, including AI coding assistants and agents (e.g., Claude Code), model APIs (e.g., Anthropic, OpenAI), and open-weight models hosted on RCC systems. Develop, maintain, optimize, and support scientific software, computational workflows, and research computing environments on RCC systems. Troubleshoot, profile, optimize, and port scientific applications to maximize performance across CPU, GPU, memory, storage, and I/O. Contribute technical expertise to faculty projects through the RCC Consultant Partnership Program and other collaborative initiatives. Contribute computational expertise to grant proposals, including scoping the AI, HPC, cloud, and storage resources committed to the project. Develop and maintain technical documentation and knowledge base resources. Contribute to the continuous improvement of RCC systems, services, operational practices, and user support processes. Solves user problems promptly and professionally. Proactively recommend appropriate RCC technologies and services. Stay current with advances in AI, HPC, GPU computing, and cloud technologies, and evaluate emerging tools for adoption at the RCC. Develops and presents technical training materials and web-based documentation. Ensures timely systems support and updates. Assists in conducting information security assessments and risk analysis of computing environment. Evaluates past and present technologies to help develop new tools. Ensures all the new tools have been through quality control reviews. Performs other related work as needed. Minimum Qualifications Education: Minimum requirements include a college or university degree in related field. Work Experience: Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline. Certifications: --- Preferred Qualifications Education: PhD in a relevant field. Technical Skills or Knowledge: Proficiency in one or more compiled programming languages (e.g., C++, C, Julia, or Fortran). Proficiency in Python or another scientific scripting language. Experience working in Linux/UNIX environments and with high-performance computing (HPC) systems. Experience with HPC job schedulers (e.g., Slurm). Experience installing, optimizing, profiling, and supporting scientific software and workloads on HPC systems. Excellent analytical, problem-solving, and communication skills, with the ability to work effectively with faculty and multidisciplinary teams. Familiarity with scientific computing libraries such as NumPy, SciPy, pandas, xarray, and scikit-learn. Experience with containers and development tools such as Docker, Apptainer/Singularity, and Git. Experience with AI/ML frameworks such as PyTorch or TensorFlow. Experience with LLM APIs and tooling (e.g., Anthropic, OpenAI, Hugging Face), AI coding assistants. Experience serving or benchmarking models on GPU clusters. Preferred Competencies Ability to translate researchers' scientific goals into computational requirements. Ability to work independently and as part of a collaborative team. Demonstrated ability to evaluate and apply emerging technologies in research computing. Application Documents C/V or resume (required) Cover letter (preferred) The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions. When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application. Job Family Research Role Impact Individual Contributor Scheduled Weekly Hours 37.5 Drug Test Required No Health Screen Required No Motor Vehicle Record Inquiry Required No Pay Rate Type Salary FLSA Status Exempt Pay Range $85,000.00 - $102,500.00 The included pay rate or range represents the University's good faith estimate of the possible compensation offer for this role at the time of posting. Benefits Eligible Yes The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook . Posting Statement The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination. Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form. All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. 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