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

Job Description
re you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work with Global Technology Applied Research (GTAR) center at JPMorgan Chase & Co.. The goal of GTAR is to design and conduct research across multiple frontier technologies, in order to enable novel discoveries and inventions, and to inform and develop next-generation solutions for the firm's clients and businesses.
We are looking for applied algorithms researchers with (i) strong publication record in quantum-inspired or randomized algorithms for optimization and machine learning and/or (ii) experience developing performant code, including using accelerators like GPUs. Experience in finance is a plus, though no prior familiarity with financial use cases is required.
Job Responsibilities:
We are looking for innovative problem solvers with a passion for advancing the state of the art of quantum-inspired algorithms. The focus of your role will be to:

• 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 your findings in scientific papers and present them at conferences
• Contribute to JPMC's IP by pursuing necessary protections of generated IP

Required qualifications, capabilities, and skills

• 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 (e.g., dequantized algorithms, tensor networks, novel techniques for Ising solvers)
  • Randomized algorithms (e.g., streaming algorithms, data sketching techniques)
  • Architectural design for efficient implementation (e.g., developing memory efficient sampling techniques, end-to-end implementation of quantum-inspired and randomized algorithms)
  • GPU programming (e.g., CUDA, SYCL)

Preferred qualifications, capabilities, and skills

• Preference is given to candidates with strong publication record (example venues include but are not limited to ICML, NeurIPS, ICLR, ISCA, HPCA, STOC, FOCS)
• No prior familiarity with finance or financial use cases is required
• Preference given to candidates who includes a link to their Google Scholar or Semantic Scholar profile in their resume.

About Us
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
About the Team
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