COMPLETE INFO & APPLY HERE: https://www.bsc.es/join-us/fellowships/19419lsicbr1
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
Key Duties
- Complete a PhD in computational biology
- Collaborate with various research groups across Europe and elsewhere
Requirements
Education
- MSc in Computer Science, Mathematics, Physics, Bioinformatics, or a related field
- BSc in Computer Science is preferred
- Essential Knowledge and Professional Experience
- Fluency in spoken and written English
Competences
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
