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Europe, United Kingdom, London

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Posted 104 days ago

Research Scientist in the Quantinuum AI team

🏢 Quantinuum

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Role Type

🧪 Scientist / Researcher

Role Focus

📈 Apply Quantum

Seniority

🌱 Internship / Entry-Level

Employer Type

🏢 Industry

This Research Scientist internship involves applying modern AI methods to address numerous challenges in designing, building, and programming quantum computers. The intern will join the rapidly growing AI team to develop tools and frameworks integrating AI techniques, such as reinforcement learning, across the quantum computing stack. Key activities include collaborating with scientists to implement new algorithms, running experiments, and presenting analysis of the experimental work.

Key Responsibilities

Help design and execute experiments combining AI and quantum computing techniques.

Work collaboratively with scientists and engineers across Quantinuum teams to implement new algorithms and software solutions.

Generate analysis and reports, and present the results of experimental work to the AI team.

Required Skills

Practical machine learning experience applied to scientific or engineering problems.

Experience using standard machine learning toolkits and pipelines, such as PyTorch.

Interest in and willingness to learn about quantum computing.

Nice-to-have Skills

Familiarity with quantum computing concepts or related fields like quantum many-body physics.

Experience in large-scale machine learning, including large language models and reinforcement learning.

Experience utilizing high-performance computing platforms, such as distributed multi-node or multi-GPU systems.

Technology Tags

Quantum ML

The primary focus is applying AI and machine learning techniques to solve hard problems in the quantum computing stack.

Optimisation

One key project explicitly involves using reinforcement learning to optimize quantum circuits.

Quantum error correction

Projects include applying ML and RL techniques for state preparation and real-time decoding related to QEC.

ML approaches

The job requires experience with practical machine learning, standard toolkits, reinforcement learning, and large language models (transformers).

Simulation algos

Projects involve training models to simulate physics problems, such as preparing ground states of molecular Hamiltonians or the Transverse-field Ising model.

Trapped ions

The role provides access to Quantinuum 's world-leading quantum computers, which are based on trapped ion technology.

HPC systems

Experience leveraging high-performance computing platforms, including distributed multi-node and multi-GPU setups, is valued for large-scale machine learning.

Source Job Description

About the Internship: Designing, building, programming, and using a quantum computer poses numerous challenges. Modern AI methods show promise in tackling these challenges, and in the AI team at Quantinuum, we are integrating AI and quantum computing as part of our company-wide AI strategy. As an intern in the London office, you will work closely with research scientists and engineers in our newly formed and rapidly growing AI team, who are leading the development of tools and frameworks applying AI techniques to quantum computing to solve hard problems in the quantum computing stack. You will also have access to Quantinuum’s world-leading quantum computers.

Information about the project: We have a variety of projects to which an intern can be assigned. Examples include: using reinforcement learning (RL) to optimise quantum circuits; using ML and RL techniques for state preparation in quantum error correction (QEC); ML for real-time decoding for QEC; training transformers to generate circuits which prepare the ground state of a particular molecular Hamiltonian; training a transformer to generate samples from a Transverse-field Ising model; using features from Quantum Topological Data Analysis to improve the performance of a classical ML model on an industrially-relevant task; and designing and training quantum generative models for which there is evidence of quantum advantage.

Key Responsibilities:

Help design and run experiments at the intersection of AI and quantum computing.

Collaborate with research scientists and engineers in the AI and other Quantinuum teams to implement new algorithms and software solutions.

Produce analysis and reports and present results of the experimental work to the AI team.

Must Have:

Experience of practical ML applied to problems in science or engineering.

Experience of standard ML toolkits and pipelines, e.g. PyTorch

Interest in, and willingness to learn about, quantum computing.

We Value:

Familiarity with quantum computing concepts, or a related field such as quantum many-body physics.

Experience in large-scale machine learning (large language models, reinforcement learning).

Experience leveraging high-performance computing (e.g. distributed multi-node, multi-GPU platforms).

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