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Los Alamos National Laboratory · 1 day ago

Postdoctoral Researcher: Agentic AI and Parallel Discrete Event Simulations

Los Alamos, NM

Full-time

Onsite

New Grad, Entry Level

Los Alamos National Laboratory is seeking a postdoctoral research associate in the field of artificial intelligence and materials science. The role involves advancing materials discovery through the integration of AI techniques and parallel discrete event simulations, while collaborating with a multidisciplinary team.

Security

Growth Opportunities

No H1B

U.S. Citizen Only

Responsibilities

Join a multidisciplinary team advancing materials discovery by combining theoretical methods, computational methods, machine learning and artificial intelligence

Explore the development of new artificial intelligence architectures, efficient training of materials models in data-scarce scenarios, and their fast inference

Conduct original scientific research through peer-reviewed publication records

Collaborate in a human-expert guided manner, driven by an agentic AI framework implemented over parallel discrete event simulations for extreme scalability

Qualification

PythonArtificial IntelligenceMachine LearningParallel Discrete Event SimulationHigh Performance ComputingGenerative AI ModelsAgentic AI FrameworksQuantized AI ModelsCommunication SkillsWriting Skills

Required

A Ph.D. in Electrical and Computer Engineering, Computer Science, Mathematics, Materials Science, Physics, or related physical sciences, completed within the last 5 years or to be completed soon

Programming and simulation experience (Python, Julia, Lua, etc.)

Demonstrated experience in conducting original scientific research through peer-reviewed publication records

Excellent communication and writing skills

Preferred

Solid background in modern artificial intelligence architectures such as LLM, TRM, transformers, various machine learning frameworks, and regression methods

Demonstrated experience in parallel discrete event simulation (PDES) methods using Python/C/C++ frameworks such as Simian, Simulus, or similar PDES engines

Experience with agentic AI frameworks, Model Context Protocol (MCP) etc

Experience with training generative or perturbative AI models, their inference in HPC environment

Research experience in quantized AI models, training, and LoRA finetuning

Research experience with using AI/ML methods for molecule discovery, drug discovery, and related materials science applications

Experience with High Performance Computing (HPC) and GPU programming, especially in the context of AI/ML. Hands-on experience running experiments on cloud-based HPC platforms especially for AI training and inference

The ability to work creatively and independently as well as learn and collaborate with experts as a part of a diverse multi-disciplinary team

Ability to adapt to new requirements for projects and be flexible enough to learn new skills