Organisation/Company University of Barcelona Department Mathematics and Computer Science Research Field Computer science Engineering Other Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions Application Deadline 10 Nov 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Permanent Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Dec 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

No deje pasar esta ocasión, inscríbase rápidamente si su experiencia y habilidades coinciden con lo que se indica en la siguiente descripción.
Offer Description

We are looking for a talented and motivated Research AI Engineer to join the Artificial Intelligence in Medicine Lab (BCN-AIM, ) at the University of Barcelona, as part of TrustAI-ES ( ), an innovative Spanish national research project funded by the Spanish Ministry of Science, Innovation and Universities (MICIU/AEI) and co-funded by the European Regional Development Fund (ERDF).

The successful candidate will contribute to the development, implementation and validation of artificial intelligence models for heart failure, with a particular focus on federated learning, Generative AI for medical image and video synthesis, and trustworthy and fair AI.

The candidate will work under the direct supervision of Dr. Polyxeni Gkontra, Principal Investigator of TrustAI-ES, Assistant Professor at the University of Barcelona and Senior Researcher at BCN-AIM. The position will also offer opportunities to collaborate on other European-funded research projects within the lab, depending on the candidate's interests, and with international academic and clinical partners.





What will you do?

- Contribute to the full AI development lifecycle, from data preprocessing and integration to model development, implementation, deployment and validation.
- Develop, implement and validate machine learning and deep learning models for cardiovascular applications, particularly heart failure.
- Contribute to the development of fair federated learning aggregation techniques and their implementation and deployment across participating hospitals.
- Work on state-of-the-art Generative AI approaches for medical image and video synthesis and their application to cardiovascular AI.
- Implement trustworthy and fair AI approaches to improve the reliability, robustness and equity of AI models.
- Collaborate with an interdisciplinary team of AI researchers, engineers and clinical experts.
- A university degree (Bachelor's, Master's or equivalent) in Computer Science, Computer Engineering, Artificial Intelligence or a related discipline.
- Proficiency in Python
- Knowledge and experience in Machine Learning and/or Deep Learning.

Desirable qualifications and experience:
- A Master's degree or PhD in Computer Science, Computer Engineering, Artificial Intelligence or a related discipline will be highly valued.
- Knowledge and experience in Federated Learning and/or Generative AI




- Experience in medical image analysis and/or artificial intelligence applications in healthcare.

We are looking for someone with strong technical skills, enthusiasm for research and medical applications of AI, and the ability to work both independently and collaboratively in an international research environment.

We offer:

- The opportunity to join a dynamic research group working at the forefront of AI for healthcare.
- Research experience within a prestigious university (1st position in Spain).
- Hands-on experience in cutting-edge research on federated learning, Generative AI for medical image/video synthesis and trustworthy AI.
- An international and multidisciplinary research environment, with opportunities to collaborate with academic and clinical partners.
- Flexible working arrangements, including the possibility of teleworking.
- The opportunity to live and work in Barcelona, one of Europe's most vibrant and attractive cities.

About the project

TrustAI-ES: Trustworthy AI for Heart Failure Risk Assessment in Spain through Federated Learning and Image Synthesis

TrustAI-ES aims to develop innovative and trustworthy AI solutions for heart failure risk assessment by leveraging federated learning and medical image/video synthesis. The project focuses on developing privacy-preserving and fair AI models that can learn from data distributed across different hospitals, without requiring the centralisation of sensitive patient information. At the same time, generative AI for medical image/video synthesis will be used to expand the available training data, particularly for under-represented groups in Spain. This is essential for ensuring algorithmic fairness and reducing bias in AI models.

📌 Research AI engineer (España)
🏢 University of Barcelona
📍 España