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Postdoctoral Researcher in Machine Learning and Artificial Intelligence for Materials Discovery
2 months ago
We are seeking a highly motivated and talented Postdoctoral Researcher to join our team at Los Alamos National Laboratory. The successful candidate will have the opportunity to engage with a dynamic, multidisciplinary research team that bridges fundamental science with applications and materials development, characterization, and testing.
Key Responsibilities- Conduct research in machine learning and artificial intelligence for materials science, with a focus on developing and applying novel methods for materials discovery and design.
- Collaborate with experimental and theoretical researchers to integrate machine learning and artificial intelligence techniques with experimental and computational methods.
- Develop and maintain high-performance computing codes and workflows for large-scale simulations and data analysis.
- Publish research results in top-tier scientific journals and present at international conferences.
- Contribute to the development of new research directions and initiatives within the laboratory.
- Ph.D. in theoretical/computational Physics, Chemistry, Computer Science, or related area completed within the last 5 years or to be completed soon.
- Strong programming skills using high-level languages such as Python.
- Experience with machine learning methods and/or applied generative AI, with a focus on materials science applications.
- Ability to work creatively and independently, as well as learn and collaborate with experts and contribute to a diverse multi-disciplinary team.
- Strong communication and language skills, as evidenced by publications and presentations.
- Experience with AI for science, science-informed machine learning, inverse problems, uncertainty quantification, transformer architectures, foundation models, or surrogate modeling.
- Experience with high-performance computing, GPU programming, parallel programming, and related paradigms.
- Experience with modern machine-learning libraries and tools, especially for training and deploying generative AI models.
- Knowledge of modern electronic structure theory codes and their application for modeling materials properties.
- Experience with high-throughput frameworks and/or cheminformatics tools.
- Competitive salaries based on the date the PhD degree requirements were completed or the degree was awarded.
- A generous benefits package, including medical, dental, and vision insurance, as well as a 401(k) plan.
- Opportunities for professional development and growth, including training and education programs.
- A dynamic and inclusive work environment, with a diverse team of researchers and scientists.
