Data Scientist in Biomedical AI – Digital Health Unit (RE1)

Reference: 434_26_LS_DHU_RE1

Job title: Data Scientist in Biomedical AI – Digital Health Unit (RE1)

About BSC

The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large-scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries.

Look at the BSC experience: BSC-CNS YouTube Channel Let's stay connected with BSC Folks!

We are particularly interested for this role in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research. In instances of equal merit, the incorporation of the under-represented sex will be favoured.

We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences.

If you consider that you do not meet all the requirements, we encourage you to continue applying for the job offer. We value diversity of experiences and skills, and you could bring unique perspectives to our team.

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, flexible 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

Applications procedure and process

All applications must be submitted via the BSC website and contain:

• A full CV in English including contact details

• A cover/motivation letter with a statement of interest in English, clearly specifying for which specific area and topics the applicant wishes to be considered. Additionally, two references for further contacts must be included. Applications without this document will not be considered.

Development of the recruitment process

The selection will be carried out through a competitive examination system ("Concurso-Oposición"). The recruitment process consists of two phases:

• Curriculum Analysis: Evaluation of previous experience and/or scientific history, degree, training, and other professional information relevant to the position. - 40 points
• Interview phase: The highest-rated candidates at the curriculum level will be invited to the interview phase, conducted by the corresponding department and Human Resources. In this phase, technical competencies, knowledge, skills, and professional experience related to the position, as well as the required personal competencies, will be evaluated. - 60 points. A minimum of 30 points out of 60 must be obtained to be eligible for the position.

The recruitment panel will be composed of at least three people, ensuring at least 25% representation of women.

In accordance with OTM-R principles, a gender-balanced recruitment panel is formed for each vacancy at the beginning of the process. After reviewing the content of the applications, the panel will begin the interviews, with at least one technical and one administrative interview. At a minimum, a personality questionnaire as well as a technical exercise will be conducted during the process.

The panel will make a final decision, and all individuals who participated in the interview phase will receive feedback with details on the acceptance or rejection of their profile.

At BSC, we seek continuous improvement in our recruitment processes. For any suggestions or comments/complaints about our recruitment processes, please contact recruitment [at] bsc [dot] es. For more information, please follow this link.

Deadline

The vacancy will remain open until a suitable candidate has been hired. Applications will be regularly reviewed and potential candidates will be contacted.

OTM-R principles for selection processes

BSC-CNS is committed to the principles of the Code of Conduct for the Recruitment of Researchers of the European Commission and the Open, Transparent and Merit-based Recruitment principles (OTM-R). This is applied for any potential candidate in all our processes, for example by creating gender-balanced recruitment panels and recognizing career breaks etc. BSC-CNS is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law. For more information follow this link