MESA is hiring at the University of New Mexico. A full-time postdoctoral position anchors the project at the Center for Advanced Research Computing (CARC) in Albuquerque, working directly with the PI and partner teams at the University of Arizona and UNC-CH/RENCI. CARC is separately hiring a Research Computing Facilitator who will work alongside the team.
01
Lead the agentic AI orchestration prototype: self-hosted LLM serving on vLLM, RAG pipelines over curated scientific metadata, and the MCP server framework — sandboxing, multi-agent orchestration, and evaluation against real science use cases from genomics to the Event Horizon Telescope.
You bring a PhD in CS or a computational science, systems-level Python, and an interest in how LLM agents should handle petabytes responsibly. Structured mentoring plan, first-author publications, and TrustedCI security review participation are part of the role.
02
Sit between researchers and the machines. Consult with PIs and their labs to scope computing needs, build and maintain Linux servers, workstations, and VMs, install and troubleshoot scientific software across Python, R, MATLAB, and C/C++, and move groups onto CARC’s HPC systems or cloud platforms when local resources run out. You will also configure AI-assisted and agent-based tools for research computing — automation, troubleshooting, and documentation — inside real security and data-governance requirements.
You bring a bachelor’s degree and at least a year of directly related experience, Linux administration (Rocky, RHEL, Ubuntu, or similar), scripting in Bash or Python, and the presentation skills to make a complicated idea land with technical and non-technical researchers alike. HPC support, cloud provisioning, GitHub collaboration, AI-agent deployment, and sensitive-data practice (CUI, FERPA) are preferred. Posted as Systems/Network Analyst 2.
The prototype runs on leveraged national infrastructure — no waiting for procurement. You join a team that already ships: the MESA MCP stack is public, installable in one line, and in use against the CyVerse Data Store today.
Easley (H100, L40S) and Hopper (A100) GPU clusters with multi-petabyte storage, on campus.
The iRODS-backed national data commons the federated mesh is built on.
Jetstream-2 GPU cloud, TACC mirrors, Open Storage Network, and NAIRR Pilot allocations.
ESIIL, NCEMS, AIIRA, and the Event Horizon Telescope drive the use cases.