PhD student in Computer Science and Bioinformatics (R1)

Centre / Institution:
Barcelona Supercomputing Center
Bioinformatics expertise:
Comparative Genomics
life science

Job description

Context And Mission

Professor Nataša Pržulj is looking for several PhD students to work in machine learning and network science. They will be developing new algorithms for computationally hard problems and applying them to analyzing large-scale molecular and patient data to aid drug discovery and personalizing treatment. The successful candidates will work on the prestigious ERC Consolidator grant of Prof. Pržulj.

The successful candidates 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 candidates will join a dynamic research group of Prof. Przulj within BSC. The students will work in a highly sophisticated HPC environment, will have access to systems and computational infrastructures, and will establish collaborations with experts in different areas.

Desired skills and expertise

Key Duties

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



  • Education
    • MSc in Bioinformatics, Computer Science, or a related field
  • Essential Knowledge and Professional Experience
  • Fluency in spoken and written English
  • Good technical skills including at least some of the following: bioinformatics, network biology, network medicine, network analytics, medical informatics, algorithms, statistics, machine learning, programming in C, C++, a scripting language and Matlab, using a parallel computing environment, scientific computing, data analysis, graph, network and complexity theory
  • Good written and verbal communication skills in English
  • Ability to work in a professional environment within a multidisciplinary and international team
  • Critical and creative thinking skills
  • Ability capacity to interact and build strong relations with a diverse members/stakeholder/staff base
  • Ability to work independently and in a team
  • Ability to take initiative, prioritize and work under set deadlines and pressure
  • Competences

Contract duration and other benefits


  • The position will be located at BSC within the Life Sciences Department
  • We offer a full-time contract, a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible hours, extensive training plan, tickets restaurant, private health insurance, fully support to the relocation procedures
  • Duration: Temporary
  • 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: asap

Required information and contact

Applications Procedure

All applications must include:

  • A motivation letter with a statement of interest, including two contacts for further references - COMPULSORY - Applications without this document will not be considered


  • A full CV including contact details



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


Diversity and Equal Opportunity Employment

BSC-CNS is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law.