Applied Research Scientist Quantum-inspired and Randomized Algorithms, Sr. Associate

JPMorgan Chase - New York, NY

Full-time

New York, NY

Credit Intermediation and Related Activities

About the position

The Applied Research Scientist - Quantum-inspired and Randomized Algorithms - Sr. Associate role at JPMorgan Chase & Co. offers an exciting opportunity to work within the Global Technology Applied Research (GTAR) center. The position focuses on advancing the field of quantum-inspired and randomized algorithms, implementing these algorithms in performant software, and providing innovative research solutions to internal project teams. The role also involves contributing to the company's intellectual property and documenting findings in scientific papers for presentation at conferences.

Responsibilities

• Solve problems innovatively with a passion for advancing the state of the art of quantum-inspired algorithms.
• Advance the field of quantum-inspired and randomized algorithms and their applications to optimization, machine learning, and financial use cases.
• Implement the developed algorithms in performant software.
• Provide novel research solutions to problems faced by internal project teams.
• Work with other researchers to document findings in scientific papers and present them at conferences.
• Contribute to JPMC's IP by pursuing necessary protections of generated IP.

Requirements

• Ph.D. degree in computer science, physics, math, engineering or related fields.
• Demonstrated research ability in quantum-inspired algorithms or related fields.
• Experience in scientific technical writing.
• Proficiency in Python or C/C++.
• Experience developing performant codes.
• Strong communication skills and the ability to present findings to a non-technical audience.
• Experience in one or more following domains: Quantum-inspired algorithms, Randomized algorithms, Architectural design for efficient implementation, GPU programming.

Nice-to-haves

• Strong publication record in relevant venues (e.g., ICML, NeurIPS, ICLR, ISCA, HPCA, STOC, FOCS).
• No prior familiarity with finance or financial use cases is required.
• Link to Google Scholar or Semantic Scholar profile included in resume.