Research Engineer position as part of the Quantum Information Group

Quantum Information Group

Deadline for receipt of applications: November 20, 2024 23:59 AoE (21 November 2024, 13:59h Europe/Madrid Time)

Quantum entanglement is central to quantum information science, with applications in secure quantum communications, precision measurements in quantum metrology, and more. This project focuses on understanding entanglement through Quantum State Tomography (QST) while addressing the significant resource demands of traditional QST methods. By integrating machine learning, such as feature importance prediction and deep neural networks, the project aims to efficiently classify entangled states and reconstruct high-dimensional quantum states from minimal information.

Additional research will explore interpretable ML techniques to identify key features that define entangled states, advancing scalable and efficient methods for quantum state characterization and potentially revealing new insights into entanglement’s role in quantum technology.

The position requires:

• Strong background in quantum information science: In-depth understanding of quantum mechanics, entanglement theory, and quantum state tomography is essential.
• Experience with machine learning and deep learning: Proficiency in classical ML and DL techniques, particularly for high-dimensional data analysis, interpretability, and feature importance methods.
• Proficiency in Python: Demonstrated experience with Python, including familiarity with ML/DL libraries such as TensorFlow, PyTorch, or scikit-learn. Knowledge of libraries for quantum computing (e.g., Qiskit, Cirq) is a plus.
• Familiarity with quantum computing frameworks: Experience or coursework with quantum computing platforms, along with understanding of their applications to quantum state characterization.
• Mathematical and computational skills: Strong foundation in linear algebra, probability, and numerical methods, along with experience in implementing complex algorithms.
• Effective communication and collaboration skills: Ability to clearly communicate technical concepts and collaborate effectively with interdisciplinary teams in English.

Equal Employment Opportunity

IMDEA Networks Institute aims to increase the proportion of women and therefore qualified female applicants are explicitly encouraged to apply. Until a balanced ratio of men and women has been achieved at the institute, preference will be given to women if applicants have similar qualifications. IMDEA Networks Institute actively promotes diversity and equal opportunities. Applicants are not to be discriminated against in personnel selection procedures on the grounds of gender, ethnicity, religion or ideology, age, sexual orientation (anti-discrimination). People with disabilities who have the relevant qualifications are expressly invited to apply.