AI Research Assistant for Lab Discovery & ML Systems

Carnegie Mellon University; Pittsburgh (Allegheny County); Sur place; USD 22 000 - 33 000; Temps partiel

Avantages offerts par ce poste

Medical, prescription, dental, and/or视

Tuition benefits

Paid time off

Life and disability insurance

Free Pittsburgh Regional Transit bus  

Family Concierge Team

Fitness center access

Résumé du poste

Carnegie Mellon University’s Department of Mechanical Engineering is seeking a Research Assistant to develop AI/ML methods for scientific lead optimization and laboratory search. You will work on large language model systems that retrieve and synthesize literature, protocols, and experimental data, integrating RAG, embeddings, and tool APIs.

The role emphasizes reproducible research workflows, human-in-the-loop review, and collaboration with interdisciplinary teams to advance AI-enabled science

Qualifications

• Bachelor’s degree in a quantitative field is required.
• Master’s degree or Ph.D. preferred.
• At least 2 years of experience in research, software, or applied ML.
• Hands-on Python and modern deep‑learning frameworks experience.
• Experience with LLM applications, RAG, and reproducible research workflows preferred.
• Experience connecting AI systems to laboratories or experimental workflows desirable.

Responsabilités

• Develop LLM- and agent-based systems for laboratory search that retrieve and synthesize literature, protocols, and data.
• Develop AI/ML methods for lead optimization including generation, ranking, and optimization.
• Build domain-adapted LLM workflows with prompt engineering and integration with predictive models.
• Create evaluation frameworks for scientific accuracy, grounding, and robustness; implement guardrails.
• Integrate AI recommendations with iterative laboratory design-build-test-learn cycles.
• Develop interfaces to query laboratory knowledge and compare candidate leads with provenance.
• Collaborate with scientists and engineers to translate requirements into AI-enabled tools.
• Maintain technical documentation, code quality, and reproducibility standards.

Connaissances

Python

ML/AI systems

LLM/RAG

Data analysis

Experiment planning

Scientific literature review

Formation

Bachelor’s degree in a quantitative field

Master’s degree or Ph.D. preferred

Outils

Vector databases

Deep learning frameworks

Python ML tools

Description du poste

Carnegie Mellon University’s Department of Mechanical Engineering is seeking a Research Assistant to develop AI/ML methods for scientific lead optimization and laboratory search. You will work on large language model systems that retrieve and synthesize literature, protocols, and experimental data, integrating RAG, embeddings, and tool APIs.

The role emphasizes reproducible research workflows, human-in-the-loop review, and collaboration with interdisciplinary teams to advance AI-enabled science