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Quantum Research, Optimization (Intern/Contractor)

Job Description

Job Title: Quantum Research, Optimization (Intern/Contractor)

Department: R&D Innovation Lab

Duration: 6 months, Mai-Oct. (Flexible)

Supervisor: Heloise Pajot, Digital Innovation Lead

Location: Palo Alto, CA or remote (USA)

Schedule: Full time / Part-time (flexible)

Compensation: Paid, compensation commensurate based on qualifications and experience

About the company

EDF (Électricité de France) is a global, integrated energy company and the world’s largest electricity producer. With 140 GW of generation capacity across more than 30 countries, EDF generates over 650 TWh of electricity for 38 million customers, and 85% of that electricity has low or no carbon emissions. With 171,000 employees worldwide, EDF is active in the entire value chain of the electric industry, including R&D, project development, generation, trading, transmission, distribution, sales, and energy services.

In the US, EDF’s operations include EDF Renewables North America, EDF Energy North America, EDF R&D, and several smaller business units. EDF R&D has 1,800 researchers and 9 labs, including three in France, EDF Innovation Lab in the US, and others globally. Their role is to provide R&D, innovation, and business development support to the EDF Group. This is done through the creation of partnerships and collaborations with leading research institutions and industries and the identification and development of innovative technologies and solutions.

EDF is at the forefront of solving complex optimization and simulation problems in the Energy Industry. For over two decades, we have been operating our own High-Performance Computers (HPC) and developing numerous calculation codes to address these challenges. Given the growing scale and complexity of the energy industry, and to anticipate tomorrow’s challenges, EDF started exploring Quantum technologies in 2017. Today our quantum team gathers 20 researchers across France, Asia-Pacific, and the US working on several applications from quantum computing for optimization, simulation, and Quantum Machine Learning (QML) to quantum sensors and post-quantum cybersecurity. Given the early stage of quantum

technology, it’s uncommon for a utility company to invest such effort in quantum research. We’re proud to be among the leaders in quantum research for the energy industry.

About the role

We are currently seeking a talented and highly motivated Quantum Research Engineer Intern/Contractor to join our Digital Innovation team in Palo Alto, CA.

In this role, you will explore the potential applications of quantum technology in addressing a wide range of energy management problems. In this field, main challenges involve managing a stock of energy for production units (such as hydroelectric plants, batteries, or nuclear units) over a time horizon with constraints that can be efficiently modeled using a state graph. Such graph relies on a discretization of the horizon over discrete time periods. Vertices represent specific time steps and stock level, while arcs represent choices of production level, i.e stock consumption, during this time period. A path through the graph determines the energy management strategy for the unit over the horizon. Efficiently solving these models is of great importance to EDF.

Recent advancements in quantum operations research have demonstrated exponential quantum advantages for pathfinding on specific regular graphs, such as welded tree graphs [1] and regular sunflower graphs [2]. These studies achieve speed-ups by efficiently preparing a superposition of states over the vertices of the graph, a principle also considered by the EDF R&D Quantum team for outage planning [3]. This previous work highlighted the potential of quantum algorithms for energy management problems but requires extending the methodology to more generic graphs. The first step in this work will be to reproduce the results from the literature to gain a deep understanding of the methodology and confirm the quantum speed-up. Subsequently, we will study the potential extension to near-regular graphs, which could be practically applicable to energy management problems.

This position offers a unique opportunity to work at the cutting edge of quantum computing applications in the energy sector. You’ll have the autonomy to drive your research, publish and present high-impact results, and join a growing community of researchers exploring quantum solutions for the energy industry.

If you have a strong technical background, a passion for Quantum Computing, and an interest in the Energy Industry, apply now and join us in shaping the future of energy!

Qualifications:

• PhD level or currently pursuing a PhD degree in Mathematics (Optimization), Physics or a relevant field
• Strong background in quantum computing, mathematics, and algorithms
• Proficient coding skills in Python or relevant languages
• Experience with quantum programming languages and frameworks such as Qiskit, Cirq, or Q#
• Knowledge on graph optimization and/or problem complexity is preferred.
• Knowledge and experience in the energy industry is a plus.
• Ability to work independently with minimal supervision.
• Strong communication skills for collaborating with international teams and partners.

Key responsibilities:

• Assess the potential of quantum approaches to demonstrate speed up for path finding problems.
• Analyzing and verifying results obtained for pathfinding problems on specific graphs in the literature.
• Extending these methods to near regular graphs relevant to the energy management field.
• Model and implement approaches on refined use cases
• Understand and apply relevant quantum code libraries
• Perform test on Quantum machines.
• Collaborate with partners in France and in the US.

All of these tasks will be related to the work already carried out by EDF in previous years. The person may perform other duties assigned.

How to Apply:

• Send your Resume to heloise.pajot@edf-inc.com with ‘Application – Quantum Research, Optimization (Intern/Contractor)’ in the subject line. Please add your availabilities and motivations in your email.

EDF Inc. is an Equal Opportunity Employer, and all qualified candidates will receive consideration for all positions without regard to race, color, age, religion, sex (including pregnancy), sexual orientation, gender identity, national origin, veteran status, disability, genetic information, or any other characteristic protect

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Bibliography :

Jianqiang Li and Sebastian Zur. Multidimensional electrical networks and their application to exponential speedups for graph problems. arXiv preprint arXiv:2311.07372, 2023.

[1] Jianqiang Li. Exponential speedup of quantum algorithms for the pathfinding problem. arXiv preprint arXiv:2307.12492, 2023. arXiv: 2307.12492 [2] Jianqiang Li, Yu Tong, 2024, Exponential Quantum Advantage for Pathfinding in Regular Sunflower Graph, arXiv:2407.14398 [3] R Griset, I Lavdas, JG Jarkovsky, 2024 State-space reduction techniques exploiting specific constraints for quantum search Application to a specific job scheduling problem, arXiv preprint arXiv:2501.0717