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Salary
$120k – $175k per year
Location
In office (Washington)
Employment
Full-Time
Overview
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Phasecraft is a British quantum algorithms company founded in 2019 by academics from Bristol and University College London. It designs algorithms that squeeze useful results from near term quantum hardware, particularly for materials and chemistry problems. The company partners with quantum hardware makers and industrial research groups.

Phasecraft is the quantum algorithms company. We are building the mathematical foundations for quantum computing applications that solve real-world problems. Founded in 2019 by Toby Cubitt, Ashley Montanaro and John Morton, we are based in London and Bristol in the UK and opened an office in Washington DC in 2024, led by Steve Flammia. In 2023 we completed a $17m Series A funding round led by leading Silicon Valley deep tech VC, Playground Global.

Phasecraft’s unprecedented access to today’s best quantum computers - through partnerships with Google, IBM, Quantinuum and QuEra - provides us with unique opportunities to develop foundational IP, inform the development of next-generation quantum hardware, and accelerate commercialization of high-value breakthroughs.

We are looking to hire a Quantum Algorithms Scientist to join our team. The ideal candidate will have experience in the theory and/or implementation of optimization algorithms for gate-model quantum computers, or in classical optimization or constraint satisfaction algorithms; or otherwise strong evidence of potential to contribute to these areas. Their work will initially focus on these topics, though they will have the opportunity to grow a portfolio of research activity across the breadth of Phasecraft’s interests. A background in quantum computing is not necessarily required, though in this case a successful candidate will have evidence of the ability to design and implement advanced algorithms for optimization and/or constraint satisfaction.

Job Description

  • Undertake theoretical and/or applied research and/or software development for near-term quantum computing applications, with an initial focus on quantum algorithms and software for combinatorial optimization and/or constraint satisfaction problems.
  • Help to author publications, presentations, patent applications and similar resulting from the research.
  • Work collaboratively in a small team made up of full-time staff and affiliated PhD students.
  • Work with stakeholders on collaborations applying quantum computing to optimization problems.
  • Other activities as required to support the growth and success of Phasecraft.

Requirements

Essential criteria:

  • Expertise in one or more of:

    o quantum information and/or computation theory

    o theory and implementation of classical algorithms for optimization or constraint satisfaction

    o quantum algorithm design and implementation

    o mathematical analysis of algorithms

  • Proven track record of working independently on research projects.
  • Deep expertise and an excellent publication track-record in relevant discipline.
  • Excellent written and verbal communication skills and the ability to disseminate research results to technical and non-technical audiences.
  • Flexibility to work across different aspects of quantum algorithms, and to work on other tasks required to support the growth and success of the company.
  • An interest in near-term quantum computing

Desirable criteria:

  • PhD (or soon to receive one) in quantum information, quantum computation theory, theoretical computer science, or closely related field.
  • Coding in quantum software development environments (e.g. Cirq, QuEST, Qiskit).
  • Experience of implementing algorithms on quantum hardware.
  • Strong publication track-record in relevant discipline.
  • Software development skills.
  • Enthusiasm for learning and novel research.

Benefits

  • The annual compensation range for this role is $120,000 - $175,000, depending on experience.
  • Health, Vision, Dental, Life Insurance.
  • 401(k) Plan with company matching.
  • Unlimited annual leave.
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