Applied Research Scientist - Quantum-inspired and Randomized Algorithms - Vice President

Are 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, plus at least 2 years of experience (industry or postdoc)


* 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.

JPMorgan Chase & Co., one of the oldest ...