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🚀 Internship

Quantum Applications Engineer Intern

🚀 Summer Internship

London

AI generated summary

  • The ideal candidate for this Quantum Applications Engineer Intern position should have a BSc/MSc or PhD in a relevant field, knowledge of quantum computing algorithms, experience with software best practices and multiple programming languages (especially Python), familiarity with Machine Learning/AI algorithms, and preferably experience with Tensor Network numerical simulation methods. Additionally, experience in quantitative risk management, technical writing, statistical analysis, predictive modeling, and conceptual modeling would be beneficial. The candidate must be self-motivated, results-oriented, professional, adaptable to change, and able to work both independently and as part of a team. Open-source contributions and code repositories would also be a plus.
  • The Quantum Applications Engineer Intern at Moody's Analytics is responsible for developing and implementing innovative solutions, algorithms, and use cases for quantum computing, collaborating with internal teams and external partners, and actively seeking ways to build the company's reputation in the field.

Summer Internship

DataLondon

Description

  • In this role you will be hands-on, evaluate current literature, participate in the research community, and develop solutions in partnership with domain experts across the company. We are looking for a person who is passionate about quantum computing.

Requirements

  • BSc/MSc in Computer Science, Engineering, Physics, Math, or related field.
  • PhD in Computer Science, Engineering, Physics, Math, or related field preferred but not mandatory.
  • Knowledge of quantum computing algorithms, particularly gate model and hybrid techniques.
  • Previous experience with software best practices, including continuous-integration pipelines, unit testing, code review.
  • Experience working with several programming languages (most importantly Python).
  • Experience with Machine Learning / AI algorithms is preferred but not mandatory.
  • Demonstrated knowledge and experience with Tensor Network numerical simulation methods, with a focus on machine learning and optimization is a plus.
  • Familiarity with Tensor Network libraries and/or relevant functions ( cuTensorNet, TeNPy or others) is a plus
  • If you have open-source contributions or your own code repositories will be a plus.
  • Relevant experience in quantitative risk management is preferred but not mandatory.
  • Experience in technical writing in a scientific or technical field.
  • Self-motivated with a willingness to learn.
  • Must be results-oriented and have a proven ability to get things done through people, including those not under direct management.
  • High level of professionalism.
  • Be able to keep up with a landscape where new data keeps flowing in rapidly and the world is constantly changing.
  • Ability to work equally well as part of a team and autonomously.
  • Experience in the following topics is a plus:
  • Performing statistical analysis.
  • Predictive modelling.
  • Conceptual modelling.
  • Creating examples, prototypes, demonstrations.

Education requirements

Currently Studying
Bachelors
Masters

Area of Responsibilities

Data

Responsibilities

  • Own and lead the conception and delivery of novel solutions to problems faced by internal project teams.
  • Develop new and improve existing Quantum Algorithms for specific applications, in the team and in collaboration with external partners.
  • Provide guidance to other groups throughout Moody’s Analytics on best practices and advanced techniques.
  • Contribute to Moody’s IP by developing innovative solutions and use cases in collaboration with our partners and clients.
  • Write white papers.
  • Scan the market / competitors / partners / research, lead client engagements to understand challenges that they are trying to address and meet with external partners to bring new ideas and technologies to Moody’s Analytics.
  • Represent the company as a technical expert on quantum computing and present research findings to audiences internally and externally. Demonstrate thought leadership as it relates to QC, and actively seek ways to build MA’s “data and risk expertise” reputation externally (white papers, speaking panels, etc.). Partner with other ML groups inside the company to find hybrid solutions and benchmarks.

Details

Work type

Full time

Work mode

office

Location

London