Quobly

About the Company

Quobly is a pioneer in the development of a fault-tolerant quantum computer based on semiconductor qubits. With a breakthrough method, Quobly addresses both techno-scientific challenges as well as industrial production, paving the way for mass production of the millions of qubits essential for practical, large-scale quantum computers. Based in Grenoble, the startup is the result of 15 years of collaborative research between internationally recognized RTOs, CEA Leti and CNRS. Founded in 2022, Quobly has brought together a team of experts from the semiconductor industry and distinguished researchers in quantum technologies. In 2023, Quobly made headlines with a seed round of 19 million euros, establishing a new record for seed funding of a European startup in the quantum sector.
Today, Quobly employs +70 people.

Listed Jobs

Company Name

Quobly

Job Title

Internship | Experimental automation of silicon spin qubits

Job Description

**Job title** Internship – Experimental Automation of Silicon Spin Qubits Engineer **Role Summary** A research internship focused on automating the tuning and calibration of silicon quantum dot (spin qubit) devices. Interns will develop machine‑learning algorithms for data labeling, synthetic image generation, validation, and predictive modeling, and may also explore neural‑network approximations of cost functions for reinforcement learning within a broader automation pipeline. **Expectations** - Pursuing a Master’s degree (or equivalent) in applied physics, computational mathematics, engineering, or related disciplines. - Strong analytical mindset and enthusiasm for quantum technology. - Ability to learn and apply ML techniques to experimental data. - Proactive, collaborative, and capable of contributing to scientific outputs. **Key Responsibilities** 1. Analyze calibration requirements for silicon-based spin qubits and design fast, wafer‑agnostic algorithms. 2. Label experimental measurement data and construct methods to generate realistic synthetic images. 3. Develop and train machine‑learning models that (a) validate generated images and (b) predict device behavior from measured and synthetic data. 4. Implement neural‑network surrogates of expensive cost functions to enable efficient reinforcement‑learning control. 5. Integrate ML solutions into the overall experimental automation workflow. 6. Assist in preparing results for publication and conference presentation. **Required Skills** - Proficiency in Python and ML frameworks (TensorFlow, PyTorch, or equivalent). - Experience with image‑based data labeling and supervised learning. - Solid foundations in numerical methods, optimization, and neural‑network training. - Knowledge of semiconductor physics and quantum dot operation is highly advantageous. - Good problem‑solving, communication, and teamwork abilities. **Required Education & Certifications** - Current enrollment in a Master’s program (or equivalent) in applied physics, computational mathematics, electrical engineering, computer science, or a closely related field. - No mandatory certifications; coursework in machine learning, quantum technology, or semiconductor device physics is preferred.

Grenoble, France

On site

31-10-2025