Postdoctoral Researcher — Multi-Agent LLM Systems
Carnegie Mellon University · Pittsburgh, PA, USA · original posting ↗
Strong eligibility and research alignment.
- ✓ Research areas matched: Multi-Agent Systems, AI Agents, Multi-Agent Learning, Large Language Models, LLM Agents, Tool-Using Agents, AI Planning, Reasoning Agents
- ✓ Required discipline(s) detected: Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering
- ✓ Skills matched: Python, PyTorch, Transformers, Multi-Agent Systems, Federated Learning, Distributed Systems, Cloud Computing, Deep Learning, Machine Learning, Computer Vision
- ✓ Skills not evidenced: Explicit tool-using agents experience, Specific runtime coordination frameworks for specialised agents
Stages: discovery → qualification → research_match → candidate_match → ranking
Qualification analysis
- Decision
- ACCEPT (confidence 0.99)
- Required fields
- Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering
- Preferred fields
- —
- Domain-specific
- —
- CS compatibility
- 100/100
The posting explicitly requires a PhD in Computer Science, Artificial Intelligence, Machine Learning, or Computer Engineering. The applicant holds a PhD in Computer Science (Artificial Intelligence), which directly satisfies one of the required disciplines.
Research match
- Alignment
- STRONG (95/100)
- Matched areas
- Multi-Agent Systems, AI Agents, Multi-Agent Learning, Large Language Models, LLM Agents, Tool-Using Agents, AI Planning, Reasoning Agents, Federated Learning, Distributed Systems, Python, PyTorch, Transformers, Deep Learning
- Missing areas
- Computer Vision, Edge AI, Intelligent Transportation Systems, Generative AI
The candidate's expertise in multi-agent AI, LLM agents, tool-using agents, long-horizon planning, reasoning, and federated learning aligns directly with the postdoc's focus on multi-agent LLM systems and distributed learning. Core technical skills (Python, PyTorch, Transformers) match the required stack. Only peripheral interests such as computer vision, edge AI, and transportation systems are not addressed by the position.
Candidate match
- Overall
- 96/100
- Matched skills
- Python, PyTorch, Transformers, Multi-Agent Systems, Federated Learning, Distributed Systems, Cloud Computing, Deep Learning, Machine Learning, Computer Vision, LangGraph, FastAPI, Docker, PostgreSQL
- Missing skills
- Explicit tool-using agents experience, Specific runtime coordination frameworks for specialised agents
- Strengths
- PhD in Computer Science (AI) directly satisfies required degree; Extensive 25+ years software and systems architecture experience; Production-level LLM pipelines and multi‑agent LangGraph deployment; Strong publication record (5 peer‑reviewed papers, high impact factor); Research interests align closely with multi‑agent LLM orchestration, federated learning, and AI planning
Original posting (stored separately from analysis, for audit)
The Language Technologies Institute seeks a postdoctoral researcher to work on multi-agent LLM systems: agent orchestration, tool-using agents, long-horizon planning and reasoning, and runtime coordination between specialised agents. The group also studies federated learning across distributed deployments. Required: PhD in Computer Science, Artificial Intelligence, Machine Learning, or Computer Engineering. Strong Python, PyTorch and transformers experience expected. Location: Pittsburgh, PA, United States.