Research Computing Consultant II – AI & HPC

getting there through hands-on guidance, workshops, documentation, and ongoing consultation.

This is an early-career role designed for someone with genuine enthusiasm for emerging technologies and a talent for translating complex tools into practical, accessible knowledge for research communities. The right candidate will be energized by community engagement and education, motivated by helping others succeed with new tools, and comfortable working across a wide range of disciplines and technical backgrounds. This is primarily a people-facing, community-oriented role for someone who wants to be at the frontier of how AI and HPC are used in academic research.

The position reports to the Director of Research Engagement and Data Science and works in close partnership with the Research Cyberinfrastructure and Research Software Engineering teams. Strong communication skills, workshop facilitation experience, and a demonstrated curiosity about AI and advanced computing tools are essential to success in this role.

Description

Dartmouth College seeks a research computing professional to serve as a computational thought partner to faculty and research teams across disciplines. This role sits at the intersection of applied data science, advanced computing, and collaborative research strategy.

The Research Computing Consultant II – AI & HPC advances Dartmouth’s research mission by enabling scalable, reproducible, and innovative computational practices. This position partners directly with faculty, postdoctoral scholars, and graduate students to shape analytical approaches, optimize computational workflows, and expand adoption of advanced research technologies.

This role is within the Research Engagement and Data Science team, reporting to the Director of Research Engagement and Data Science and working in close collaboration with research computing infrastructure colleagues and campus partners.

Required Qualifications - Education and Yrs Exp

Bachelors plus 3-5 years' experience or equivalent combination of education and experience

Required Qualifications - Skills, Knowledge and Abilities

• Bachelor’s degree in computer science, data science, information science, a natural or social science, or a related field; Master’s degree preferred, particularly in a computationally oriented discipline.
• Minimum of one year of experience in research computing support, academic technology, data science facilitation, or a related role.
• Working knowledge of large language models and AI-assisted tools, including practical experience applying them in research or analytical contexts.
• Familiarity with high-performance computing environments, including job submission and basic workflow management.
• Foundational proficiency in Python or R for data analysis and workflow support.
• Demonstrated ability to explain complex technical tools and concepts clearly to non-specialist audiences.
• Experience designing or delivering technical workshops, training sessions, or instructional materials.
• Strong interpersonal and communication skills, with genuine enthusiasm for community engagement and researcher support.
• Ability to work on campus multiple days per week; this is a hybrid-eligible role requiring consistent in-person presence to support the research community.

Preferred Qualifications

• Master’s degree in data science, computer science, information science, computational science, or a related quantitative discipline.
• Hands-on experience with cloud computing platforms used in research contexts (e.g., AWS, Google Cloud, Azure, or institutional cloud environments).
• Demonstrated ability to evaluate, advise on, and communicate the appropriate use and limitations of AI tools in academic or research settings.
• Background developing asynchronous educational content, documentation, or tutorials for technical audiences.
• Working knowledge of Linux-based systems and HPC workload scheduling tools (e.g., Slurm).
• Active or emerging engagement with research computing, AI, or academic technology communities through presentations, working groups, or professional networks.
• Proficiency in data visualization tools and experience creating accessible, publication-quality figures or interactive outputs.
• Grounding in research data management practices and awareness of compliance and privacy considerations in AI and cloud computing contexts.
• Exposure to the academic research lifecycle, including familiarity with grant processes, research workflows, or scholarly publishing norms.

Key Accountabilities

AI and HPC Researcher Facilitation – 35%

• Partners with faculty and research labs to assess computational and AI-related needs and identify appropriate tools, platforms, and workflows suited to their research context.
• Advises researchers on effective and responsible use of large language models, AI-assisted analysis tools, and cloud-based AI services in their research workflows.
• Guides faculty and research teams in getting started with Dartmouth’s high-performance computing environments, including account setup, job submission, resource selection, and basic troubleshooting.
• Helps research teams identify when cloud computing platforms are appropriate alternatives or complements to on-premise HPC, and supports onboarding to relevant cloud research environments.
• Consults with researchers on responsible AI use, including awareness of limitations, reproducibility considerations, data privacy, and ethical dimensions of AI-assisted research.
• Collaborates with the Research Cyberinfrastructure and Research Software Engineering teams to communicate faculty needs and contribute to improved researcher experience on HPC and cloud platforms.
• Supports Dartmouth-affiliated research partnerships and enterprise collaborations by extending AI and HPC facilitation services as appropriate.

Outreach, Education, and Community Engagement – 35%

• Designs and delivers workshops, short courses, and training sessions covering AI tools for research, HPC usage, cloud computing, reproducible workflows, and related topics for faculty and research lab audiences.
• Develops and maintains asynchronous learning resources including tutorials, how-to guides, documentation, and reference materials that enable self-directed researcher adoption of AI and HPC tools.
• Hosts regular office hours and drop-in consultation sessions to provide accessible, approachable support for researchers at all stages of AI and HPC adoption.
• Proactively engages faculty and research labs across departments and disciplines to understand emerging needs and build awareness of available tools and services.
• Evaluates emerging AI tools, models, and platforms relevant to academic research and communicates their potential value and limitations to the research community in accessible terms.
• Contributes to the development of onboarding programs for new researchers joining Dartmouth’s computing ecosystem.
• Represents the Research Computing and Data team at departmental meetings, research events, and relevant campus forums to build relationships and expand service visibility.

Data Science and Research Lifecycle Support – 20%

• Applies a data science perspective to facilitation work, helping researchers connect AI and HPC tools to their broader analytical and data management workflows.
• Supports data organization, preprocessing, and structuring tasks to prepare research datasets for AI-assisted or HPC-accelerated analysis.
• Contributes to the development of data visualizations and summary outputs that help research teams communicate findings and progress.
• Provides guidance on responsible and compliant use of research data in AI and cloud computing contexts, including awareness of relevant institutional and regulatory requirements.
• Promotes documentation and reproducibility as foundational practices in AI-assisted and computationally intensive research.

Professional Development and Institutional Contribution – 10%

• Actively monitors the evolving landscape of AI tools, large language models, cloud platforms, and HPC technologies as they apply to academic research practice, and regularly shares knowledge with the team.
• Maintains and expands technical proficiency in relevant tools and platforms to ensure facilitation guidance remains current and credible.
• Serves as a collegial resource to team members and contributes to a collaborative, service-oriented environment.
• Promotes equitable and inclusive access.

Demonstrates professionalism and collegiality through actions, interactions, and communications with others appropriate to an environment that is welcoming to all. Performs other duties as assigned.