Postdoctoral Appointee – Advancing AI and LLMs for Scientific Discovery jobs in United States
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Argonne National Laboratory · 1 day ago

Postdoctoral Appointee – Advancing AI and LLMs for Scientific Discovery

Argonne National Laboratory is seeking a highly motivated Postdoctoral Appointee with expertise in artificial intelligence and machine learning, specifically in developing Large Language Models for scientific applications. The role involves working with advanced computing resources and a multidisciplinary team to advance LLM capabilities for complex scientific challenges.

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Responsibilities

Design and optimize multimodal LLMs to encode, fuse, and reason over heterogeneous scientific data from diverse modalities such as numerical tables, text, and images
Conduct large-scale LLM training, including pretraining, fine-tuning, RL tuning, and domain-specific adaptation on HPC systems
Design and implement fine-tuning and RL strategies to optimize LLM alignment, performance, and reliability for scientific applications
Develop and deploy autonomous LLM agents capable of reasoning, planning, and decision-making to support complex scientific workflows
Implement alignment, safety, and reliability frameworks to ensure LLM outputs are accurate, trustworthy, and robust in scientific contexts
Evaluate and benchmark LLM reasoning, cognitive capabilities, and generalization to support robust analysis, interpretation, and decision-making
Apply conformal prediction and uncertainty quantification techniques to generate reliable confidence estimates and risk assessments for LLM outputs
Disseminate research findings through publications in peer-reviewed journals and conferences
Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork

Qualification

Artificial IntelligenceMachine LearningLarge Language ModelsHigh-Performance ComputingMultimodal Data HandlingRespectSafetyImpactTeamworkIntegrity

Required

Recently completed Ph.D. (typically within the last 0–5 years, or soon-to-be-completed) in Computer Science, Applied Mathematics, or a closely related field
Design and optimize multimodal LLMs to encode, fuse, and reason over heterogeneous scientific data from diverse modalities such as numerical tables, text, and images
Conduct large-scale LLM training, including pretraining, fine-tuning, RL tuning, and domain-specific adaptation on HPC systems
Design and implement fine-tuning and RL strategies to optimize LLM alignment, performance, and reliability for scientific applications
Develop and deploy autonomous LLM agents capable of reasoning, planning, and decision-making to support complex scientific workflows
Implement alignment, safety, and reliability frameworks to ensure LLM outputs are accurate, trustworthy, and robust in scientific contexts
Evaluate and benchmark LLM reasoning, cognitive capabilities, and generalization to support robust analysis, interpretation, and decision-making
Apply conformal prediction and uncertainty quantification techniques to generate reliable confidence estimates and risk assessments for LLM outputs
Disseminate research findings through publications in peer-reviewed journals and conferences
Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork

Company

Argonne National Laboratory

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Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management.

H1B Sponsorship

Argonne National Laboratory has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2022 (6)
2021 (2)

Funding

Current Stage
Late Stage
Total Funding
$41.4M
Key Investors
Advanced Research Projects Agency for HealthUS Department of EnergyU.S. Department of Homeland Security
2024-11-14Grant· $21.7M
2023-09-27Grant
2023-01-17Grant

Leadership Team

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Raeanna Sharp- Geiger
COO
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Paul Kearns
Laboratory Director
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Recent News

Inside HPC & AI News | High-Performance Computing & Artificial Intelligence
Inside HPC & AI News | High-Performance Computing & Artificial Intelligence
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