Researcher in Advancing Quantum Machine Learning Algorithms Term Devices Industri

Eurecat is the second Research & Technology Organisation in Spain and one of the largest applied research and technology transfer organisation in Southern

Europe. It brings together the experience of more than 800 professionals who generate an annual turnover of 69 million euros and provides services to more than 2,000 companies. Eurecat integrates advanced digital capabilities and experience in biotechnology, industry and sustainability and collaborates with industry in R&D+I activities and projects, offering advanced scientific and technological services and specialized knowledge to respond effectively to the technological needs of very different business sectors, accelerating innovation, reducing both risks and spendings on scientific and technological infrastructures.

The technology center participates in more than 200 large national and international consortium projects of high strategic R&I, has 230 patents and 10 spin-offs. Eurecat has eleven centers in Catalonia and presence in Madrid, Malaga and Chile.

The
Quantum Computing Research Group
at Eurecat develops advanced quantum software solutions for tackling complex problems in areas such as quantum machine learning and optimization.

They provide access to quantum simulators, hardware, and offer consultancy services to help companies adopt quantum technologies. Their team combines expertise in quantum physics, computer science, and software development. They also collaborate on projects to promote R&D in practical quantum computing applications.

EURECAT Quantum Computing Research Group offers a position for an experienced researcher to develop the following research project:
Advancing Quantum Machine Learning Algorithms for Near Term Devices with Industrial Applications

This position is included in the Ramon Llull-AIRA Postdoctoral Programme and co-funded by the Marie Sklodowska-Curie programme under Horizon Europe.

Theme Briefing:

The proposed research theme aims to advance quantum machine learning (QML) algorithms tailored to near-term, noisy intermediate-scale quantum (NISQ) devices, with a particular focus on generative models. Building on our recent work on shallow instantaneous quantum polynomial-time (IQP) circuits as quantum circuit Born machines for random graph generation, we will further develop this line into a general framework for scalable quantum generative modeling.

Methodologically, the project will explore hybrid QML architectures that (i) train predominantly on classical hardware via statistically motivated loss functions, while (ii) delegating sampling and certain subroutines to quantum processors and high-fidelity quantum simulators (up to 34 qubits available at EURECAT). We will investigate encoding schemes and circuit designs that are both expressive and hardware-efficient, studying their robustness to noise, their ability to capture higher-order correlations in complex networks, and their practical performance against strong classical baselines.

Collaboration and secondments with the QML-CVC group will ensure a strong link to computer vision and representation learning, enabling cross-fertilization between quantum generative models for graphs, images, and spatio-temporal data, and paving the way for realistic, industry-oriented use cases of QML in the NISQ era.

In order to formalize their application, applicants must complete the registration forms before March 2026
, making sure they provide all the information requested through the link below:

• Researchers must be in possession of a doctoral degree at the deadline of the co-funded programme’s call
• Candidates must not have resided or carried out their main activity (work, studies, etc.)
  in Spain for more than 12 months in the three years immediately before the deadline of the open call.
• Proficiency in English

Application Requirements :

In order to formalize their application, applicants must complete the registration forms, making sure they provide all the information requested through the link below:

• Digital copy of all academic certificates (Bachelor/Master/PhD). Candidates who have not yet formally been awarded the doctoral degree must include a letter from the doctoral school indicating that the thesis has been submitted and an estimated date for the thesis defence.
• Research Proposal

Applications submitted directly to Eurecat will not be taken into consideration. All applications must be submitted exclusively through the Ramon Llull – AIRA Postdoctoral Programme via the following link Ramon Llull AIRA Open Calls

Make sure you are including all the required documents checking the Call Documents & Templates section in the programe website.