Quantum Graph Algorithm Developer

Job description

About

PASQAL designs and develops quantum processors (QPUs: Quantum Processing Units) and associated software tools. Their innovative technology makes it possible to handle use cases that are currently beyond the reach of the most powerful supercomputers.
QPUs are extremely energy-efficient, and will help to significantly reduce the carbon footprint of the HPC industry.

About us:

· 
French Tech 2030 Laureate

· 
Enabled by Nobel Prize-winning technology

· 
A team made of scientists, quantum engineers as well as deeptech enthusiasts ;)

· 
In direct competition with the world's biggest players (Google - Microsoft - IBM - Amazon...)

· 
130 million Euros raised

Job Description

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

As part of our strong growth, we are recruiting a Quantum Graph Algorithm Researcher to reinforce our Quantum Machine Learning team. In this context, you will contribute to demonstrate the quantum advantage in machine learning on graphs. In this role, you will work on cutting-edge methods combining quantum physics and graph machine learning and participate in creating new algorithms that will run on Pasqal's Quantum Processor Unit.

With a dual background in both physics and machine learning engineering, your responsibilities will include:

·  Designing and implementing quantum-enhanced graph machine learning models on classical computers and quantum hardware
·  Collaborating with the team to research and develop advanced techniques for applying quantum mechanics to graph machine learning problems
·  Developing classical components of the machine learning pipelines, such as data preprocessing, post-processing and integration with quantum hardware or simulation platforms
·  Keeping up-to-date with advancements in both machine learning and quantum computing fields
·  Collaborating with hardware engineers to apply your quantum algorithm on Pasqal quantum hardware

About you

You hold a PhD in Applied Mathematics, quantum physics, computer vision or any related field, and have around 1-3 years of experience in Machine Learning. 

Hard skills : 

·  Strong taste for Applied Mathematics and graphs, and a keen interest in deep tech and new technologies
·  Solid foundation in quantum physics, mathematics or computer science
·  Algorithms development, numerical simulations
·  Proficient in Python, other programming language is a plus
·  Report / documentation writing
·  Experience on machine learning, graph machine learning is a plus
·  Notions of quantum computing, atomic physics and optics are a plus
·  English fluency

Soft skills : 

·  Team player 
·  Interpersonal skills
·  Proactive 
·  Autonomous 

What we offer

·  Offices in Massy, France
·  Occasional remote work (1 to 2 days per week)
·  Type of contract: permanent 
·  A dynamic and close-knit international team
·  A key role in a growing start-up
·  Free time to train and go to conferences/meetups

Recruitment process

·  An interview with our Talent Acquisition Specialist of 45'
·  A technical test 
·  An technical interview with the Hiring Manager of the team (if test conclusive) 
·  A meeting with the team in our Massy office
·  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.

Additional Information

·  Contract Type: Full-Time
·  Location: Massy
·  Education Level: PhD and more
·  Experience: > 1 year
·  Possible partial remote