Context And Mission

The Barcelona Supercomputing Center – Centro Nacional de Supercomputación, BSC-CNS, is Europe’s leading center for supercomputing research.

The successful candidate will work in a highly advanced HPC environment, with access to state-of-the-art computational infrastructures, and will collaborate with experts from clinical, academic, and technological institutions at national and international levels.

The Digital Health Unit, led by Dr. Paula Petrone, applies artificial intelligence to healthcare with the goal of developing innovative, clinically meaningful, and scalable solutions that can have a real impact on patients and health systems.

This position will contribute to the LiverAim project, a European collaborative project focused on improving liver disease risk assessment.

The selected candidate will work on AI-based approaches for liver risk prediction using clinical, biochemical, lifestyle, biomarker, and FibroScan-related data.

In parallel, the candidate will contribute to other strategic research lines of the Digital Health Unit, particularly the development and application of vision-language models, multimodal AI, foundation models, and generative AI approaches for healthcare.

We encourage applications from all genders and candidates from underrepresented groups.

Key Duties

- Develop AI models for liver risk assessment using clinical, biochemical, lifestyle, biomarker, and FibroScan-related data
- Work with heterogeneous biomedical datasets, including structured clinical data, imaging-derived variables, biomarkers, and other health-related data sources.
- Develop predictive models using machine learning, deep learning, multimodal learning, transformers, foundation models, and generative AI approaches.
- Contribute to Digital Health Unit projects involving medical image analysis, vision-language models, multimodal clinical data, and biomedical foundation models.
- Collaborate with clinicians, biomedical researchers,



data scientists, and project partners to define clinically relevant questions and validation strategies.
- Contribute to robust, reproducible, interpretable, and clinically meaningful AI pipelines.
- Support the preparation of scientific publications, project deliverables, technical documentation, and presentations for consortium meetings and scientific forums.
- Contribute to the translation of AI methods into clinically relevant digital health tools.

Requirements

- Education
- Master’s degree in Computer Science, Data Science, Biomedical Engineering, Mathematics, Physics, Bioinformatics, Computational Biology, or a related field.

- Essential Knowledge and Professional Experience

- Hands-on experience in machine learning and/or deep learning applied to biomedical or healthcare data.
- Strong programming skills in Python and experience with common data science and deep learning libraries, such as PyTorch, TensorFlow, scikit-learn, pandas, NumPy, or equivalent.
- Experience working with structured clinical data, biomarkers, imaging-derived variables, or multimodal biomedical datasets.
- Knowledge of model development, validation, performance metrics, and reproducible AI pipelines.
- Interest in clinically oriented AI, with emphasis on developing models that are robust, interpretable, and useful for healthcare applications.
- Ability to work with heterogeneous real-world clinical data, including missing data, variable harmonisation, and cohort differences.

- Additional Knowledge and Professional Experience

- Experience with liver disease, metabolic disease,



cardiometabolic risk, epidemiology, or clinical prediction modelling.
- Experience with medical image analysis, biomedical signal processing, or image-derived quantitative biomarkers.
- Experience with multimodal AI, transformers, foundation models, large language models, vision-language models, or generative AI.
- Experience with model explainability, uncertainty quantification, fairness assessment, or clinical AI validation.
- Experience working with clinicians, hospitals, biomedical research groups, or health data infrastructures.
- Familiarity with data protection, ethical requirements, and regulatory considerations in biomedical AI.

- Competences

- Excellent analytical and problem-solving skills.
- Ability to work independently and proactively in a research environment.
- Strong communication skills and ability to interact with multidisciplinary teams.
- Capacity to translate clinical questions into computational problems and computational results into clinically understandable outputs.
- Good organisational skills and ability to contribute to project deliverables and timelines.
- Fluency in English.

Conditions

- The position will be located at BSC within the Life Sciences Department
- We offer a full-time contract (35h/week), a good working environment, a highly stimulating environment with state-of-the-art infrastructure, adaptable working hours, extensive training plan, restaurant tickets, private health insurance, support to the relocation procedures
- Duration: Open-ended contract due to technical and scientific activities linked to the project and budget duration
- Holidays: 22 days of holidays + 6 personal days + 24th and 31st of December per our collective agreement
- Salary: we offer a competitive salary commensurate with the qualifications and experience of the candidate and according to the cost of living in Barcelona
- Starting date: asap

📌 Data Scientist in Biomedical AI – Digital Health Unit (Barcelona)
🏢 Barcelona Supercomputing Center
📍 Barcelona