"Computational Scientist for AI"

Position Summary

The Center for Research Computing (CRC), a division of the Office of Information Technology (OIT), is dedicated to delivering and supporting world-class research computing services for the Rice University community. We are seeking a computational scientist to assist researchers using our HPC systems, specifically to support the use of GPUs, AI software, and research computing workflows for optimal performance. This role aligns with the University's strategic goal of expanding AI capabilities.

This position supports advanced artificial intelligence (AI), machine learning (ML), and deep learning (DL) research across a wide variety of academic disciplines. The person in this role will collaborate with faculty, postdoctoral researchers, and graduate students to develop and optimize GPU-based applications for generative AI, complex simulations, and digital twins on high-performance computing (HPC) systems. The role includes technical support, training, and strategic contributions to Rice University's institutional AI initiatives.

An ideal candidate for this position is a GPU-first AI/ML computational scientist with deep, hands-on experience optimizing and scaling CUDA and PyTorch/TensorFlow workloads on HPC clusters (e.g., Slurm, containers), adept at building and tuning LLMs/generative models and simulations, and effective collaborating within a major research-oriented institution.

Workplace Requirements

This position is an on-site (in-person) role. A hybrid work arrangement may be considered after the probationary period. Per Rice policy 440, work arrangements may be subject to change.

Hiring Range

This is a full-time, benefits-eligible position, and the proposed salary range is $95,000 to $105,000 annually, depending on qualifications and experience. *Exempt (salaried) positions under FLSA are not eligible for overtime.

Minimum Requirements

• Bachelor's degree in computer science, computational chemistry, materials science, engineering, or a related field In lieu of the education requirement, additional related experience above and beyond what is required, on an equivalent year-for-year basis, may be substituted
• 3+ years of experience in artificial intelligence, machine learning, GPU workflows, and/or HPC environments that support AI/ML and GPU research computing workflows In lieu of the experience requirement, additional related education above and beyond what is required, on an equivalent year-for-year basis, may be substituted.

Skills

• Understanding of research computing and data systems, including high-performance computing, web-based data platforms, large-scale data storage, and networking technologies
• Expert knowledge of UNIX/Linux systems
• Proficiency in Python, C++, R, or other programming languages used in scientific research involving machine learning, deep learning, and parallel computing
• Experience with MPI/OpenMP and/or CUDA, PyTorch, and TensorFlow
• Experience with AI/ML software installation, testing, and tuning
• Experience using GPUs to accelerate AI or ML workflows
• Strong written and oral communication skills
• Ability to establish effective, ongoing relationships with faculty, students, staff, management, external institutional partners, and other stakeholders
• Strong time management and prioritization skills
• Ability to execute highly complex or specialized projects
• Strong problem-solving skills
• Depth of knowledge in the technical discipline or domain needed to deliver projects

Preferences

• Advanced degree (Master's level or PhD) with domain or applied research computing skills
• Experience with large language models (LLMs), transformer architectures, and multimodal AI
• Familiarity with Docker, Slurm, Jupyter, CUDA, and/or other HPC/AI tools
• Experience with digital twin technologies
• Experience running tightly or loosely coupled simulations on parallel or GPU systems
• Understanding of density functional theory (DFT), finite element methods (FEM), Monte Carlo simulations, or multiscale modeling
• Experience with outreach, user engagement, and training non-technical or multidisciplinary audiences on technical subjects
• Familiarity with on-premise and/or commercial cloud platforms for AI

Essential Functions

• Consult with researchers to determine their needs
• Perform computerized data processing operations and statistical analyses of research data
• Perform computing programming, debugging, and documentation; assist in interpretation and reporting of results
• Collaborate in problem assessment, analysis, and development of computational methods or procedures
• Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques
• Optimize and extend algorithms, analysis pipelines, and software to ensure effectiveness and scalability of computing infrastructure
• Provide consultation and expertise with computer applications for research problems
• Perform outreach and training activities to ensure the relevance of current and new service developments
• Contribute to technical proposal preparation and/or presentations
• Mentor assigned staff and/or graduate students
• Manage projects of moderate size, scope, and complexity
• Participate in CRC incident response; while infrequent, this may involve evening or weekend work
• Perform other duties as assigned

Additional Responsibilities

• Support faculty and students on a variety of AI/ML research projects, including large language models, generative AI, and neural networks
• Develop scalable AI applications using frameworks such as PyTorch, TensorFlow, and Keras
• Optimize models for GPU-accelerated HPC environments
• Integrate AI tools and techniques into research computing workflows
• Provide consultation, training workshops, and documentation for AI tools
• Collaborate on grant proposals and interdisciplinary research
• Monitor, tune, and troubleshoot AI workloads and applications
• Participate in professional organizations and attend relevant conferences, such as SIG-HPC, the Campus Research Computing Consortium, and PEARC

Special Instructions to Applicants

Applicants should attach a resume and cover letter in PDF format to the Supporting Documents section of the application.

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