Researcher - Quantum Machine Learning & Quantum Information

The Role

The Researcher in Quantum Machine Learning or Quantum Information will be a member of Terra Quantum’s AI Applied Research team. This team is at the forefront of conducting both fundamental and applied research in the field of quantum machine learning. Although the Researcher will focus on innovating in quantum machine learning, the role involves translating research findings into practical algorithmic software solutions.

The Researcher is expected to closely monitor and analyse scientific and industrial trends and needs across short‑term, mid‑term, and long‑term horizons, specifically within the quantum technology and machine learning sectors, to guide the development and implementation of hybrid quantum‑classical algorithms.

The Researcher in Quantum Machine Learning plays a role in driving excellence within their team. They are not only detail‑oriented but also possess a remarkable capacity for enthusiasm. By demonstrating commitment and passion for the mission, they inspire their team members to contribute to making quantum technologies widely accessible and to effect positive change globally.

• Fundamental research in quantum machine learning
  • Developing quantum machine learning algorithms for different data processing tasks, e.g. time series, routing and planning, image, graph data, or natural language processing
  • Exploring state‑of‑the‑art approaches in quantum machine learning
  • Analysing parametrised quantum circuits in their capacity to learn via a hybrid quantum‑classical optimisation loop
  • Utilising metrics such as the Fisher information matrix, the effective dimension, and Fourier term accessibility for parametrised quantum circuit ansatz analysis
  • Improving the trainability of parametrised quantum circuits through layer‑wise batch‑entropy regularisation and similar techniques
  • Interpreting and explaining quantum machine learning models; analysing the flow of information through different architectures of quantum neural networks
  • Researching and understanding where the quantum brings benefit to machine learning
  • Developing data encoding and data processing techniques for different types of quantum computers
  • Writing research papers for scientific journals
• Efficient implementation of quantum machine learning algorithms
  • Executing quantum machine learning algorithms on QPUs, e.g. of QuEra, IonQ, Rigetti, and IBM Q
  • Adjusting and improving implementation of hybrid quantum neural networks for different QPUs
  • Exploring and testing the best ways to hybridise classical machine learning solutions with quantum machine learning
  • Understanding the efficient interaction of hardware (CPU, GPU) and software (PyTorch, Pennylane)
  • Assisting in the development of our quantum machine learning SDK
  • Optimising, at least theoretically, the code of hybrid quantum‑classical machine learning solutions for faster execution
• Supporting industry projects implementation
  • Bringing in novel ideas based on industry needs in time‑series, routing and planning, GenAI, and natural language processing tasks
  • Brainstorming on possibilities of quantum machine learning algorithm applications to our client’s industry problems
  • Working on finding a theoretical or empirical advantage of using hybrid quantum‑classical machine learning in industrial problems
  • Assisting in writing applied industry research papers for scientific journals

• Currently pursuing or recently completed a degree in computer science, physics, mathematics, or an equivalent subject
• Experience in one or more quantum programming languages (Qiskit, Pennylane, Cirq, etc.)
• Experience working with variational quantum algorithms for machine learning
• Experience working with classical machine learning algorithms
• Basic knowledge in Python, PyTorch and Tensor Flow
• Experience working with QPUs is optional
• Familiarity with quantum information theory is optional
• Familiarity with tensor‑network techniques is optional
• Goal‑oriented, analytical and able to work independently
• Flexible, proactive, and creative with the ability to work in a team
• Highly motivated and resilient with the ability to work interdisciplinarily
• Proficiency in written and spoken English
• Applicants must have…