Hybrid Quantum NLP Software Internship bei Quantinuum
Quantinuum · Oxford, Vereinigtes Königreich · Hybrid
- Junior
- Optionales Büro in Oxford
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 [1]. 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 [3]; graphical interfaces for lambeq.
References:
[1] Kartsaklis et al. lambeq: An Efficient High-Level Python Library for Quantum NLP (https://arxiv.org/abs/2110.04236)
[2] Coecke et al. Mathematical Foundations of a Compositional Distributional Model of Meaning (https://arxiv.org/abs/1003.4394)
Must have:
Desirable:
About Us:
Science Led, Enterprise Driven – Accelerating Quantum Computing
Quantinuum is the world’s largest integrated quantum company, pioneering powerful quantum computers and advanced software solutions. Quantinuum’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With approximately 500 employees, including 370+ scientists and engineers, Quantinuum leads the quantum computing revolution across continents.
Quantinuum recently secured $300m in funding, visit our news pages to learn more about this and other Quantinuum scientific breakthroughs and achievements: https://www.quantinuum.com/news
Please note that employment with us is subject to successfully passing our background checks. We are an inclusive equal opportunity employer. You will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, or veteran status.
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