Applied Mathematician/Computational Scientist

1 day ago


Menlo Park, California, United States SRI International Full time
Job Overview

At SRI International, we are seeking a highly skilled Applied Mathematician/Computational Scientist to join our team. This role will involve conducting research and development in the areas of mathematics of generative AI models, scalable graph analysis methods, and network sciences. The ideal candidate will have experience in implementing scalable software associated with these areas and a strong publication track record.

Key Responsibilities
  • Develop and train generative AI models, including fine-tuning large language models.
  • Design and implement distributed algorithms for large graphs.
  • Collaborate with the team to develop research ideas and instantiate approaches in prototype software.
  • Lead the experimental evaluation of these ideas, compile results, and communicate the results in presentations.

Requirements
  • PhD in Applied Mathematics, Computer Science, or Engineering with a focus on computational sciences or a related area.
  • US Citizenship and ability to obtain/maintain a security clearance.
  • Strong publication track record and expertise in algorithm development associated with artificial intelligence, graph theory, statistical methods, and quantum platforms.
  • Experience with smart manufacturing is a plus.

What We Offer

The salary range for this position is $111,474-$164,110. SRI International offers a competitive benefits package, including a 401(k) plan, health insurance, and paid time off. We also offer opportunities for professional growth and development, as well as a collaborative and dynamic work environment.

SRI International is an independent nonprofit research institute headquartered in Menlo Park, California. We create and deliver world-changing solutions for a safer, healthier, and more sustainable future. Our team focuses on the development of new algorithms for a wide variety of exciting applications, including supply chain networks, social graphs, optimization of generative AI models, material failures, and biological systems.


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