PhD Studentship in Integrative Computational Network Biology - TranSYS Project

Barcelona Supercomputing Center
Spain Barcelona


Prof. Natasa Przulj is looking for a PhD student in Bioinformatics and Computer Science, funded by EU Horizon 2020 TranSYS Innovative Training Networks (ITN) project. The PhD student will work on developing and applying new network science and machine learning algorithms to biomedical data and problems. The new algorithms will be devloped for computationally hard problems and applied to analyze large-scale molecular and patient data to aid drug discovery and personalizing treatment (precision medicine). The successful candidates will work on the ITN TranSys EU grant described at , which offers a competitive salary and compensation package to the successful candidate. When applying for this post, please select Early Stage Researcher 9, ESR 9, at .

The successful candidate will complete a PhD in Computer Science, which will address developing and applying sophisticated machine learning and network science models and algorithms. The algorithms will be carefully tuned to extract relevant 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 that would enable mining the data for new biological and medical insight that would further lead to improving diagnostics, discovering new biomarkers, improving patient stratification and treatment, personalizing treatment and facilitate rational drug development. The successful candidate will join a dynamic research group of Prof. Przulj within BSC, currently having 8 PhD students and two post-docs. The PhD student will work in a highly sophisticated HPC environment, will have access to systems and computational infrastructures, and will establish collaborations with experts in different related areas via secondments within the TranSYS ITN consortium.

TranSYS ITN, coordinated by K. Van Steen (KU Leuven), will recruit a total of 15 ESRs (Early Stage Researchers) to highly skilled jobs in this new area of Systems Health, developing tools and approaches to exploit large and complex datasets, to advance Precision (Personalised) Medicine in several disease areas. The TranSYS training programme and experience of different international research environments cuts across traditional data and life sciences silos. The emphasis on translational research will support new collaborations between academics and the pharma and health analytics sectors. Our ESR projects will advance the state of the art on biomarker discovery, improve understanding of disease-specific molecular mechanism and target identification for optimal diagnostics, disease risk and treatment management, refine data generation and their management (including warehousing, disease specific and standardised approaches for data processing, visualisation and model development) leading to improved clinical study design, clinical sampling and more targeted therapeutics. This European ITN (Innovative Training Network) will internationalise participants, and leverage EC (European Commission) and industry sponsorship, to structure and expand the unique training programme and advance emerging research areas, combining wet-lab, clinical and Big Data resources with computational and modelling know-how.

Key Duties

Complete a PhD in computational biology
Collaborate with various research groups across Europe and elsewhere


MSc in Computer Science, Mathematics, Physics, Bioinformatics, or a related field
BSc in Computer Science is preferred

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

Fluency in spoken and written English

Start date

As soon as possible

How to Apply

Applications Procedure

In order to apply to the project ESR9, you must:

Follow this link (it will give you more information about the project, key time, and general procedure):
Click on Apply Here.
Complete all the fields, and select as first choice "ESR9: Patient-centric data integration framework for highly dimensional data Host: BARCELONA SUPERCOMPUTING CENTER (SPAIN) PhD awarding institution: UNIVERSITAT DE BARCELONA Lead Supervisor: N Pržulj"
Upload your CV, a motivation letter, and additional documents if available.


The vacancy will remain open until suitable candidate has been hired. Applications will be regularly reviewed and potential candidates will be contacted.