OverviewData Scientist In Ai For Cardiology – Digital Health Unit (Re2) at Barcelona Supercomputing Center (BSC-CNS).
Join to apply for the Data Scientist in AI for Cardiology – Digital Health Unit (RE2) role at Barcelona Supercomputing Center.Reference: 650_25_LS_DHU_RE2.
Job title: Data Scientist in AI for Cardiology – Digital Health Unit (RE2).
About BSCThe 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, and is involved in European HPC initiatives.
The mission of BSC is to research, develop and manage information technologies to facilitate scientific progress.
BSC combines HPC service provision and R&D; in computer and computational science across life, earth and engineering sciences.
The organization values diversity and inclusion and invites applications from all genders and underrepresented groups.Context and MissionThe Digital Health Unit applies artificial intelligence to healthcare with the goal of delivering innovative solutions that make a true impact for patients.
This position is part of a collaboration with the AI in Cardiology Group at Hospital de la Santa Creu i Sant Pau.
The aim is to develop AI solutions in cardiology that advance healthcare practice and contribute to product-oriented applications with real-world clinical impact.Key DutiesDevelop AI Models For Cardiology, With Emphasis On:Analysis of cardiac signals using advanced signal processing methodsMedical image analysis in cardiologyIntegration of biomarkers into predictive modelsApplication of deep learning, transformers, foundational models, and generative AI approachesCollaborate with clinical researchers and cardiologists to co-design and validate AI toolsContribute to the development of product-ready applications for use in healthcare settingsEnsure models are robust, explainable, and clinically relevantPublish and disseminate results in scientific and innovation forumsRequirementsEducationMaster's degree in Computer Science, Biomedical Engineering, Mathematics, Physics, or related fieldsPhD is welcome (plus), but not requiredEssential Knowledge And Professional Experience3 to 5 years hands-on experience in deep learning applied to biomedical data, with emphasis on deep-learning, transformers and foundational modelsStrong background in signal processing, particularly for biomedical signals such as cardiac dataProven expertise in medical image analysis, preferably in cardiology or related healthcare domainsSolid programming skills (Python or similar) and use of deep learning libraries (PyTorch, TensorFlow)Strong interest in developing healthcare applications with real clinical impactAdditional Knowledge And Professional ExperienceExperience collaborating with clinical partners or working on healthcare datasets is an advantageFamiliarity with biomarkers or multimodal data integration is desirableFluency in English, Catalan, and SpanishCompetencesExcellent problem-solving and analytical skillsAbility to collaborate in multidisciplinary teams (engineers, clinicians, researchers)ConditionsThe position will be located at BSC within the Life Sciences Department.
Benefits include a full-time contract (37.5 h/week), a stimulating environment with state-of-the-art infrastructure, adaptable working hours, training plan, restaurant tickets, private health insurance, relocation support, and an open-ended contract related to project and budget duration.Holidays: 23 paid vacation days plus 24th and 31st of December per the collective agreement.
Salary: competitive and commensurate with qualifications and experience.Applications procedure and processAll applications must be submitted via the BSC website and include a cover letter in English specifying the areas/topics of interest, and two references.
Applications without this document will not be considered.
The selection will be conducted through a competitive examination system (Concurso-Oposición).
The Recruitment Process Consists Of Two PhasesCurriculum Analysis: evaluation of experience, degree, training, and relevant information (40 points)Interview phase: evaluation of technical competencies, knowledge, skills, and personal competencies (60 points).
A minimum of 30 points out of 60 is required to be eligibleThe recruitment panel will be composed with gender-balanced representation.
Additional steps include a personality questionnaire and a technical exercise.
Feedback will be provided to all participants.
The process follows Open, Transparent and Merit-based Recruitment (OTM-R) principles and equals opportunity employment.For questions about recruitment processes, please contact the provided address.
The vacancy remains open until a suitable candidate is hired.
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