Students@SC programming brings together two days of technical training, career development, and professional connection for students exploring high performance computing (HPC), artificial intelligence (AI), and the many career paths that connect them.
Over two days, participants will work hands-on with modern HPC and AI concepts, learn from professionals across industry, academia, national laboratories, and startups, and build practical skills for navigating the next stage of their education and career.
Student Programming
Sunday–Monday, 15–16 Nov 2026
8:30 am–4:30 pm CT
See sessions below for details.
Student Programming ChairTom Papatheodore, Advanced Micro Devices, Inc. (AMD)
Student Programming Vice ChairJack Morrison, NVIDIA
Student Programming Committee MembersDaniel Barry
Md Hasanur Rashid
Subil Abraham
Open to all registered SC attendees. Pre-registration may be required for select sessions.
Build confidence, expand your network, and see where your skills can take you.
Student Programming is designed for undergraduate and graduate students interested in high performance computing, artificial intelligence, scientific computing, research software engineering, advanced networking, systems, and related careers.
Students do not need to have a fully defined career path before attending. These sessions are intended to help participants explore options, ask questions, and build practical skills for the future.
Start your SC26 experience with a full-day, hands-on introduction to high performance computing and artificial intelligence.
This workshop will help students build practical familiarity with the tools, concepts, and workflows used in modern HPC and AI development. Through guided exercises, students will explore how to work in advanced computing environments, run computational workloads, and understand how AI applications connect with large-scale computing systems.
The workshop is designed for students with a range of backgrounds. Whether you are encountering HPC for the first time or looking to strengthen your foundation, this session will help you build confidence using technical computing resources.
Sunday, November 15
Additional details, including slides and any required setup instructions, will be announced closer to the conference.
Technical skills are only part of building a career in HPC and AI. This half-day workshop helps students understand the career landscape, strengthen their professional presence, and prepare for conversations with employers, mentors, and graduate programs.
Students will explore the range of roles available across HPC and AI, including research, systems and infrastructure, GPU and performance engineering, research software engineering, applied machine learning, and developer relations. The workshop will also cover how to evaluate graduate school options, build strong resumes and portfolios, search for roles effectively, and prepare for interviews and offers.
Monday, November 16
8:30 am–1:30 pm CT
Welcome!
Begin the day with a short orientation to the career workshop and afternoon coaching sessions. Students will have a chance to reflect on their goals, see how the day’s sessions fit together, and start thinking about the questions they want to explore with speakers, panelists, coaches, and peers.
What HPC & AI Careers Actually Look Like
This session provides an overview of the HPC and AI career space organized by role type, including research, systems and infrastructure, GPU and performance engineering, applied machine learning, research software engineering, and developer relations. Employer types such as industry, national laboratories, academia, and startups are used as a secondary lens, along with a candid comparison of sector tradeoffs such as compensation, autonomy, stability, and publication freedom.
Panel and Q&A
A moderated panel featuring 4-5 professionals from academia, industry, national laboratories, and startups. Panelists will share their career journeys, discuss what they look for when hiring, and answer audience questions. The session includes both moderated discussion and open Q&A.
Graduate School & Degrees Needed for Roles
A candid discussion of when a master’s degree, PhD, or neither is the right choice based on career goals. This session covers the practical realities of funding, advisor selection, and the questions students should ask before committing to a program.
What You Can Do Now
Practical guidance on building a professional presence through resumes, GitHub portfolios, and online profiles, tailored to HPC and AI roles. Students will work through hands-on exercises such as rewriting resume bullet points using an impact-driven framework and auditing their GitHub profiles.
Search, Interviews, & Negotiations
This session covers where HPC and AI jobs are posted, including where they are not always obvious, how to read job postings critically, what to expect from the technical interview pipeline, and the fundamentals of evaluating and negotiating an offer.
Boxed Lunch & Debrief
Students will collect boxed lunches while a short presentation covers how to get maximum value from a brief professional conversation, directly preparing them for the afternoon coaching sessions. Remaining time will be used for student lightning talks and to address audience questions collected throughout the morning.
Recap & Commitments
An interactive recap of the day’s key takeaways through a “Myth or Reality?” exercise, followed by a commitment moment where students identify one specific action they will take in the next seven days. The session closes with a brief hands-on window for students to take one small action before leaving the room.
Connecting the Dots
The workshop concludes by connecting the day’s content back to concerns students raised in the opening polls. Students will receive a curated resource page with resume templates, portfolio examples, job boards, graduate school guidance, interview preparation materials, and conference recommendations. Logistics for the afternoon coaching sessions will also be reinforced.
The afternoon career coaching sessions give students the opportunity to participate in focused career conversations with HPC and AI professionals.
These 10-15 minute, one-on-one sessions are designed to give students personalized guidance on career questions, resumes, graduate school decisions, job searches, technical growth, and professional next steps. Students will select their preferred coach in advance and are encouraged to come prepared with specific questions and goals so they can make the most of each conversation.
1:30–4:30 pm CT
Pre-registration will be required for career coaching. Details will be announced closer to the conference.
Tom Papatheodore
Advanced Micro Devices, Inc. (AMD)
Tom Papatheodore is a Senior Member of Technical Staff at AMD, where he manages the AI & HPC Clusters in the AMD University Program. The clusters are Slurm-based systems with multi-GPU compute nodes built on AMD EPYC CPUs and AMD Instinct GPUs, providing academic researchers and educators with the resources they need for AI and scientific computing research and university teaching. Before AMD, Tom was an HPC Engineer at the Oak Ridge Leadership Computing Facility (OLCF), where he developed GPU benchmarks for system acceptance and regression testing, managed the user training program, and supported researchers running on some of the world’s fastest supercomputers. He earned his PhD in physics from the University of Tennessee.
Jack Morrison
NVIDIA
Jack Morrison is a Senior AI/ML HPC Cluster Engineer at NVIDIA, where he drives improvements to research clusters and advocates for the researchers who use them. He has spent his career building and supporting high-performance computing environments across systems large and small, on premises and in the cloud. He is passionate about bridging the gap between scientific users and system administrators, helping researchers make effective use of complex systems. Before NVIDIA, Jack led automated testing, continuous integration, and HPC infrastructure efforts supporting the development of Omni-Path networking technologies at Cornelis Networks. He previously worked as an HPC Engineer at Rescale and the Oak Ridge Leadership Computing Facility, where he supported scientists on leadership-class supercomputing systems.
Doctoral Candidate, University of Delaware
Md Hasanur Rashid (Hasan) is a doctoral candidate in Computer Science at the University of Delaware, where his research focuses on data-intensive high-performance computing systems, including storage optimization, workflow orchestration, adaptive I/O tuning, quality-of-service management, and machine learning for systems. He is serving the SC26 student program as an AD/AE Committee Member and Student Volunteers Reviewer, and has been involved with the SC community as a lead student volunteer at SC23, a student volunteer at SC21, SC22, and SC24, and a technical papers reproducibility committee volunteer since SC24. His work has appeared in the Supercomputing Workshops, IPDPS, and CCGrid, and he has worked with Pacific Northwest National Laboratory and Lawrence Berkeley National Laboratory on HPC systems research. Hasan is especially interested in helping students connect systems research with practical HPC skills, research mentoring, and real scientific workflows.
Oak Ridge National Laboratory (ORNL)
Subil Abraham is a High Performance Computing Engineer in the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory. He supports researchers doing cutting edge scientific work across a wide range of domains on some of the world’s fastest supercomputers. He provides training, documentation, troubleshooting for individual users and projects, and also serves as the subject matter expert for the usage of containers on the HPC systems in the Facility. He also serves as the main user support liaison for users of the Gaea supercomputer, primarily used for research and development of weather and earth system models by the National Oceanic and Atmospheric Administration. He earned is MS in Computer Science and Applications from Virginia Tech.
Daniel Barry
University of Tennessee, Knoxville
Daniel Barry is a research scientist with the Performance Tools Group in the Innovative Computing Laboratory at the University of Tennessee, Knoxville (UTK). His research interests include performance-monitoring tools, benchmarking methodologies, optimizing applications, and numerical methods for data science. Daniel received his BS in Computer Engineering at the UTK, as well as his PhD in Data Science and Engineering, for which he was advised by Dr. Jack Dongarra. Daniel has been involved with the HPC community ever since competing with UTK in the 2013 Student Cluster Competition.
If you have questions contact the Students@SC Programming Committee. We’d be happy to help.
