Post-docs in Machine Learning for Biomedical Multi-Omic Data Analysis in Precision Medicine (R2/R3)

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 ERC Consolidator and other 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 further 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.

Key Duties

- Conduct high-quality research
- Publish in high-impact journals and conferences
- Present research at national and international conferences and meetings
- Collaborate with various research groups across Europe and elsewhere
- Help supervise PhD and MSc students
- Participate in grant writing and organizational activities
- Participate in educational and outreach activities


- PhD, MSc and BSc in a quantitative discipline are required (physics, mathematics, computer science, engineering, bioinformatics, or similar)

Essential Knowledge and Professional Experience
- Good academic and publication record for the career stage
- Fluency in spoken and written English

Additional Knowledge and Professional Experience
- Good technical skills including at least several of the following: machine learning, algorithms, data analysis, graph, network and complexity theory, scientific computing, statistics, programming in C, C++, a scripting language and Matlab, using a parallel computing environment, bioinformatics, network biology, network medicine, network analytics, medical informatics

- Good communication skills
- Ability to work in a professional environment within a multidisciplinary and international team


- The position will be located at BSC within the Life Sciences Department
- We offer a full-time contract (37.5h/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: 23 paid vacation days plus 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: November

Applications procedure and process

All applications must be made through the BSC website and contain:

- A full CV in English, including contact details
- A Cover Letter with a statement of interest in English, including two contacts for further references - Applications without this document will not be considered