Fast Atom Imaging with Deep Learning Internship

About Pasqal

PASQAL designs and develops Quantum Processing Units (QPUs) and associated software tools.
Our innovative technology enables us to address use cases that are currently beyond the reach of the most powerful supercomputers; these cases can concern industrial application challenges as well as fundamental science needs.
In addition to the exceptional computing power they provide QPUs are highly energy efficient and will contribute to a significant reduction in the carbon footprint of the HPC industry.

Job Description

Pasqal designs and develops neutral-atom quantum computers that use rubidium atoms as qubits. To perform quantum computation these qubits must be read out which is achieved by detecting the fluorescence emitted by the atoms using a camera. The task is then to detect from the images whether an atom is emitting light or not with high fidelity as fast as possible. The constraints are as follows:

• The fluorescence images of the atoms may be subject to various optical aberrations and noise
• The detection must be as fast as possible
• The position and arrangement of the atoms may vary

As an intern you will be joining the Register team. Their role is to prepare the atoms in user-defined positions for the computations that will occur in the QPU. They study and work on optimizing and developing new methods to efficiently capture atoms and put them in the correct positions detecting them with high fidelities and cooling them down.

Your role and activities will be the following:

• Implement atom detection methods based on deep learning (neural networks for object detection YOLO SSD etc.)
• Implement deep learning based denoising methods for fluorescence images
• Design experiments and scripts to test evaluate and benchmark methods and hyperparameters
• Generate dataset of fluorescence images from real atoms in various conditions
• Implement and test the best performing methods on a real Quantum Processing Unit (QPU)
• Optimize the pipeline and the model inference speed (Neural Network Compression: pruning quantization Model Compilation: TensorRT etc...)
• Read State-of-the-Art paper to review the best published methods currently existing in the literature
• Interface with hardware settings (camera)

About you

You are Master 2 student in Artificial Intelligence Signal Processing Computer Science Applied Mathematics with some focus on AI and ML looking for an an end-of-study internship. You have the following skills:

Hard skills:

1. Development:
   • Python and a bit of experience with libraries like numpy pandas torch
   • Basic knowledge of version control (mostly git)
   • Basic shell knowledge (stuff like cd/mkdir/ssh is already great)
2. Knowledge in Computer Vision (both ML and classical) is a strong plus
3. Experience with Linux (any distribution) or willingness to dive into the ecosystem is a plus
4. Good level of spoken and written English

Soft skills:

• Curiosity and willingness to learn new things
• The usual suspects: Autonomy organization communication
• Ability to focus on a complex problem and deep dive into it
• Hands on

What we offer

• Offices in Massy-Palaiseau and Paris
• Type of contract: internship
• A dynamic and close-knit international team

Recruitment process

• An interview with our Talent Acquisition Specialist (30).
• A technical interview with our Hiring Manager (45/1hr)
• An offer

PASQAL is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace as inclusion and diversity are essential to achieving our mission. We encourage applications from all qualified candidates regardless of gender ethnicity age religion or sexual orientation.