Job offer
Role details
Job location
Tech stack
Job description
- Design and implement pilot studies for the different Use Cases in the project.
- Integrate Knowledge Graphs (KGs) with AI agents to ground decisions in structured data and fine-tuning multimodal models.
- Implement advanced reinforcement learning from human feedback (RLHF) and active learning models
- Support validation and deployment across diverse Use Case settings
- Assist in creating human-centric evaluation frameworks and intuitive visualizations for the Agentic system end-user.
- Collaborate with multi-disciplinary teams, including clinicians and regulatory experts
The research projects: You will join our AI for cardiology team, as part of ongoing projects such as AIXPERT (https://aixpert-project.eu) and DataTools4Heart (https://www.datatools4heart.eu), funded by the European Commission and some coordinated by our lab. In these projects, we are developing new trustworthy AI solutions for personalised medicine approach to tailor the care models in the field of cardiovascular diseases. The project will build on a unique set of big data repositories, real-world hospital data, trustworthy AI methods, computational tools and clinical results from major EU-funded projects in cardiology leveraging federated learning. Should you join our team, you will collaborate with several technical and clinical partners within and outside Europe (e.g. in the Netherlands, United Kingdom, Greece, Spain, Belgium, France, Germany, Portugal, Peru, Tanzania, Czechia, Turkey).
The Group:
The successful candidate will join the Artificial Intelligence in Medicine Lab (www.bcn-aim.org), which is an integral part of the University of Barcelona's Faculty of Mathematics and Computer Science. It is a young and dynamic research lab, highly active in international projects, and composed of >20 enthusiastic academics, researchers, students and research managers, with expertise in data science, machine/deep learning, biomedical informatics, biomedical ethics, and health-related applications. The research team has an established track record in coordination and participation in national, European and international projects in biomedical data science and medical AI (e.g. EuCanImage, LongITools, HealthyCloud, RadioVal, DataTools4Heart, Youth-GEMs, HappyMums, AIMIX, AI4HF)., The selection is made through the evaluation of the curriculum, with an overall score of zero (0) to ten (10) points. The minimum score is five (5) points. The evaluation criteria are the following:
-
Suitability of the candidate to the main function to be carried out
-
Curricular experience
-
Professional knowledge and skills
The tribunal, in its constitutive session, assesses the CVs of the candidates presented. Selection process
A resolution of adjudication is issued to the person who, having passed the selection procedure, obtains the highest score and publishes the prioritised list of applicants who have passed the selection process, indicating the scores obtained, for subsequent recruitment, if necessary.
Additional comments
The candidate proposed for hiring must accept the job offer within 5 working days from the date of notification of the selection.
Priority will be given to people with disabilities (Law 89/2015 of June 2, reserve of quota 2% in favour of people with disabilities in companies of 50 or more people).
Be aware that the starting date sets in this offer is an estimate date. The official starting date will depend on the bureaucratic time that will take the preparation of the labour contract and presentation of the necessary documents to be hired by the selected candidate.
Requirements
We are looking for a highly skilled AI engineer to join our team at the Artificial Intelligence in Medicine lab (www.bcn-aim.org) within the University of Barcelona. We are looking for candidates with an MSc (or equivalent) in a relevant field, such as computer engineering, artificial intelligence, data analytics, or computational intelligence, who have a strong technical background. The selected candidate will contribute to the development of an adaptable, situation-aware AI-agentic platform designed to enhance the explainability, accountability, and transparency of GenAI-powered systems., * Macher's degree in Data Science, Computer Science, Biomedical Engineering, or related field
- Proficiency in Python
- Strong experience with machine learning and deep learning, preferably in healthcare
- Familiarity with FAIR data principles and ethical AI practices
- Good team spirit and participation to the lab's scientific life
- Enthusiasm about research and medical applications of AI
- Aptitude to work independently and meet deadlines., Research Field Computer science
Education Level Master Degree or equivalent, Master Degree or equivalent
Research Field Other
Education Level Master Degree or equivalent
Skills/Qualifications
-
Master's Degree (Computer Science, Computer Intelligence, AI, etc.)
-
Excellent English Specific Requirements
-
Federated learning environment
-
Proficiency in Python
-
Machine/deep learning
Languages ENGLISH
Level Excellent
Research Field Computer scienceEngineeringOther
Years of Research Experience 1 - 4
Benefits & conditions
- A dynamic position in beautiful Barcelona and its Mediterranean climate.
- Research experience within a prestigious university (1st position in Spain).
- Cutting-edge research in AI for healthcare in one of the most dynamic research groups in Europe (10 active projects including an ERC grant).
- An international research environment with a multi-cultural team representing all continents.
- Opportunities to collaborate with international and interdisciplinary collaborators as part of the European projects.
- Flexible working hours, with possibility to telework.
