Post-Doc In Ai For Biomedical Multi-Omic Data Analysis For Cancer Precision Medicineai4S Sa-613

Job Reference: 515_24_LS_ICONBI_R3
Position: Post-doc in AI for Biomedical Multi-Omic Data Analysis for Cancer Precision Medicine (R3) - AI4S
Closing Date: Monday, 30 September, 2024
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, 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 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.
We are particularly interested 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: 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 aim is to utilize them to understand the structure of the data, enabling more efficient mining for new biological and medical insights 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, working in a highly sophisticated HPC environment with access to systems and computational infrastructures, and establish collaborations with internationally renowned experts in related areas.
The funding for these actions/fellowships comes from the European Union Recovery and Resilience Facility - Next Generation, within the framework of the General Invitation by the public business entity Red.

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