VHIR – Biostatistics Technician
Provide biostatistical support and services to research groups across the Vall d’Hebron Campus, including:
participation in project kick-off and methodological meetings,
advising on study design, statistical methodology and analysis strategies.
Perform data management activities, including the preparation, validation and documentation of research datasets.
Conduct biostatistical and analytical analyses, including the application of machine learning techniques where appropriate, and prepare the corresponding technical and statistical reports.
Support researchers in the interpretation and communication of results, including participation in meetings where study findings are discussed.
Draft service proposals and associated budgets, in coordination with BIDU procedures and institutional guidelines.
Contribute to the definition, standardization and continuous improvement of analytical workflows and best practices within BIDU.
Collaborate closely with other BIDU profiles (bioinformatics, data science, AI and project management) to ensure methodological consistency and effective data integration across projects.
Participate in training, knowledge-sharing and capacity-building activities in line with the BIDU Training Plan.
Ensure compliance with institutional procedures, quality systems and data governance principles.
📌 Tipus d’oferta: Contracte de tècnic
👤 Perfil buscat:
University degree in Statistics, Mathematics, Data Science, Artificial Intelligence, Bioinformatics, Health Sciences, Biomedical Engineering, or a related field.
Professional proficiency in Catalan, Spanish, and English.
Minimum of 2 years of professional experience (or equivalent) performing tasks related to data science, biostatistics, statistical analysis, or biomedical data analysis.
Solid background in biostatistics, including descriptive and inferential statistics, regression models, survival analysis, and multivariate and longitudinal analysis.
Proven proficiency in statistical and analytical programming languages, particularly Python and/or R, including their use for data preparation and analysis, and implementation of machine learning and AI-based analytical approaches in biomedical or health-related research contexts.
Practical experience in data management and analytical workflows, including data cleaning and preprocessing, and transformation and preparation of research datasets.
Ability to produce technical and statistical reports and to communicate results clearly to non-technical audiences.