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Internship

Internship QNLP

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Quantinuum

•

6d ago

🚀 Off-cycle Internship

Oxford

AI generated summary

  • You need an MSc or PhD in Quantum Computing or AI, Python expertise, and knowledge of QML and ML libraries. UK work rights required. Desired skills: NLP experience, open-source contributions, web programming, tensor-based NLP knowledge.
  • You will design & develop add-ons for lambeq, enhancing its Quantum Machine Learning models & discourse-level text representation.

Off-cycle Internship

Data, Software Engineering•Oxford

Description

  • The Applied Quantum NLP Research team in Quantinuum is seeking two interns for a 3/6-month project on Quantum Software Engineering, based at the Oxford office. Quantinuum's Oxford team works on quantum models of natural language, and has developed the open-source Python library lambeq

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

Education requirements

Masters
PhD

Area of Responsibilities

Data
Software Engineering

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.

Details

Work type

Full time

Work mode

hybrid

Location

Oxford