Machine Learning - Postdoctoral Researcher

About the role

The Machine Learning Postdoctoral Researcher will contribute to fundamental R&D in machine learning and statistical methods in support of different projects related to AI Safety & Security, Foundation Models in areas such as material science or bio assurance, and uncertainty quantification for deep learning models.

Responsibilities

• Research, design, implement, and apply advanced machine learning methods for multiple applications in a collaborative scientific environment.
• Participate with project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex problems stemming from national security applications.
• Propose and implement advanced analysis methodologies, collect and analyze data, and document results in technical reports and peer-reviewed publications.
• Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.

Requirements

• Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA).
• Recent Ph.D. in Machine Learning, Optimization, Computer Science, Mathematics or a related field.
• Demonstrated ability and desire to obtain substantial domain knowledge in fields of application to enable effective communication with subject matter experts, and to identify novel, impactful applications of machine learning.
• Experience developing, implementing and applying advanced statistical or machine learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, or similar as evidence through medium to large scale deep learning models and experiments.
• Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software in relevant venues (NeurIPS, ICML, ICLR, CVPR, AAAI, AISTATS, UAI, KDD, JMLR, Nature etc.).
• Experience with scientific programming in the Python ecosystem as evidence through software artifacts, such as deep learning models, workflows, simulations, or similar.
• Experience with one or more of the following areas of deep learning: large language models, graph neural networks, multimodal models, generative models, robustness, explainable AI.

Qualifications

• Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA).
• Recent Ph.D. in Machine Learning, Optimization, Computer Science, Mathematics or a related field.
• Demonstrated ability and desire to obtain substantial domain knowledge in fields of application to enable effective communication with subject matter experts, and to identify novel, impactful applications of machine learning.
• Experience developing, implementing and applying advanced statistical or machine learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, or similar as evidence through medium to large scale deep learning models and experiments.
• Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software in relevant venues (NeurIPS, ICML, ICLR, CVPR, AAAI, AISTATS, UAI, KDD, JMLR, Nature etc.).
• Experience with scientific programming in the Python ecosystem as evidence through software artifacts, such as deep learning models, workflows, simulations, or similar.
• Experience with one or more of the following areas of deep learning: large language models, graph neural networks, multimodal models, generative models, robustness, explainable AI.

Skills

• Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflows.
• Demonstrated technical leadership in fields related to machine learning, such as mentorship or managing teams.
• Experience or interest in scientific applications, such as, material science, climate science, etc.

Benefits

• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)

Pay

$138,480 Annually

Schedule

Not specified