Machine Learning Postdoctoral Researcher
4 weeks ago
Los Alamos National Laboratory (LANL) is seeking a highly motivated postdoctoral researcher to join our team in machine learning. The successful candidate will work in conjunction with a small team of Ph.D. staff scientists as part of a research project focused on building optimally rotation-invariant neural nets.
This new class of machine learning models is built on tensor algebra and Lie group theory and contains a complete and independent set of rotation-invariant feature descriptors. The postdoctoral researcher will be expected to publish results of the work in high-impact peer-reviewed journals and present at well-known conferences.
Requirements:- Ph.D. in mathematics, computer science, data science, computational science, materials science, or a related discipline completed within the last 5 years.
- Strong track record of peer-reviewed publications within mathematics, computer science, data science, computational science, materials science, or related disciplines.
- Good presentation, oral, and written communication skills.
- Experience with computer programming and applied mathematics.
- Expertise in data science and/or machine learning with direct experience using deep neural networks, convolutional neural networks, and/or graph neural networks.
- Experience with computer vision, image classification, and/or image processing.
- Expertise with group theory, in particular with Lie Groups.
- Experience designing neural network architectures.
- Experience with molecular dynamics for materials science or chemistry.
- Experience with materials microstructure.
- Strong experience with Python programming and machine learning frameworks for neural networks such as PyTorch.
- Demonstrated experience in interdisciplinary science, especially in the areas mentioned above.
The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.
Los Alamos National Laboratory is an equal opportunity employer and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regard to race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal laws and regulations.
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