The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses Mare Nostrum, 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 Euro HPC 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.

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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.

Professor Nataša Pržulj is looking for several post-docs to work in machine learning (ML) informed by network science for mining big biomedical data. They will be developing new ML algorithms for computationally hard problems and applying them to analyzing large-scale, heterogeneous molecular (multi-omic) and patient data to aid drug repurposing and personalizing treatment choices. The successful candidates will work on the prestigious research grants of Prof. Pržulj.

The successful candidates will address developing and applying sophisticated machine learning and network science models and algorithms for biomedical real-world data. The models and algorithms will be carefully designed and tuned to extract new biological and medical knowledge from systems-level, real-world molecular and medical data. The aim is to utilize them to understand the structure of the data, which would furhter enable more efficient mining of the data for new biological and medical insight, that would lead to improving diagnostics, discovering new biomarkers, improving patient stratification and treatment, personalizing treatment and facilitating rational drug development. The successful candidates will join the dynamic research group of Prof. Przulj within BSC. The candidates will work in a highly sophisticated HPC environment, will have access to systems and computational infrastructures, and will establish collaborations with internationally renowned experts in different related areas.

The funding for these actions/fellowships and contracts comes from the European Union Recovery and Resilience Facility - Next Generation, within the framework of the General Invitation by the public business entity Red.es to participate in the talent attraction and retention programs within Investment 4 of Component 19 of the Recovery, Transformation, and Resilience Plan.
For more information, please check: https://www.bsc.es/join-us/excellence-career-opportunities/ai4s

"La financiación de estas actuaciones/becas y contratos, procede del Mecanismo de Recuperación y Resiliencia de la Unión Europea-Next Generation, en el marco de la Invitación General de la entidad pública empresarial Red.es para participar en los programas de atracción y retención del talento dentro de la Inversión 4 del Componente 19 del Plan de Recuperación, Transformación y Resiliencia.
Para más información: https://www.bsc.es/join-us/excellence-career-opportunities/ai4s "