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Internship QNLP

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Quantinuum

2mo ago

Applications are closed

  • Internship
    Full-time
    Off-cycle Internship
  • Data
    Software Engineering
  • Oxford

Requirements

  • MSc or PhD in Computer Science, Quantum Computing, AI, or a similar topic.
  • Excellent knowledge of Python, OOP, and software engineering principles
  • Familiarity with Quantum Machine Learning and variational quantum algorithms.
  • Knowledge of ML and QML libraries such as PyTorch, TorchQuantum, or PennyLane
  • This position also requires you to have the existing right to work in the UK.
  • Desirable skills:
  • Published work in NLP, QNLP, AI, or SE
  • Contributions to open-source projects
  • Web programming skills
  • Knowledge of tensor-based NLP approaches, such as the DisCoCat framework , and tensor networks.
  • Familiarity with mathematical models of meaning and category theory

Responsibilities

  • The project will be supervised by Dr Dimitrios Kartsaklis, Head of Applied QNLP Research in Quantinuum, and it will involve the design and development of add-ons for lambeq that extend the functionality of the package in aspects such as: Quantum Machine Learning models, platforms and functionality; support of quantum circuits that represent text at the discourse level, as proposed in the DisCoCirc framework; graphical interfaces for lambeq.

Quantinuum

Science led and enterprise driven, we’re accelerating quantum computing to solve the world’s most pressing challenges.

Technology
Industry
201-500
Employees
2021
Founded Year

Mission & Purpose

Science led and enterprise driven, Quantinuum unites Cambridge Quantum’s best-in-class software with Honeywell Quantum Solutions’ high-performing trapped-ion hardware. We are scaling quantum computing and developing applications today to solve the world’s most pressing challenges.