Machine Learning Postdoctoral Research Staff Member

Key Skills

Deep Learning, Julia, MLOps tools, Python Programming, PyTorch, R Programming, Stan, TensorFlow

Job Description

We have an opening for a Postdoctoral Research Staff Member to contribute to fundamental R&D into machine learning and statistical methods to solve important problems stemming from the Laboratory's national security mission areas. You will work as part of collaborative, multidisciplinary teams to develop and deploy new machine learning methodology to support a variety of application areas, including materials science, high energy physics, predictive biology, and more. These positions are in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate.

In this roll you will

• Research, design, implement, and apply advanced machine learning methods for multiple applications in a collaborative scientific environment.
• Actively 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.
• Contribute to grant proposals and collaborate with others in a multidisciplinary team environment, including academic and industrial partners, to accomplish research goals.
• Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
• Perform other duties as assigned.

Qualifications

• Ph.D. in Machine Learning, Statistics, Computer Science, Mathematics or a related field.
• Demonstrated ability and desire to obtain substantial domain knowledge in fields of application in order to communicate effectively 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, stan, or similar.
• Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software.
• Advanced analytical problem-solving and decision-making skills needed to craft creative solutions and independently solve complex problems.
• Experience with scientific programming in at least one high level language such as Python/R/Julia.
• Experience with one of the following areas of deep learning: foundation models, robust ML, physics-constrained ML, sequential design, multimodal models, generative models, transfer learning, self-supervised learning, point cloud learning, MLOps/ML engineering.

Qualifications We Desire

• Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods.
• Demonstrated technical leadership in fields related to machine learning, such as mentorship or managing teams.
• Experience developing or running numerical simulations of complex scientific or engineering processes.