Phd Student in Computational Biophysics and Machine Learning

**Job Reference**:

- 596_25_LS_ESB_R1

**Position**:

- PhD student in computational biophysics and machine learning (R1, FPI)

**Closing Date**:

- Thursday, 16 October, 2025

**Reference**: 596_25_LS_ESB_R1

**Job title**: PhD student in computational biophysics and machine learning (R1, FPI)

**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, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing 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 in order 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.

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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.

**Context And Mission**

The lab was created in 2025, when Dr. R. Gonzalo Parra started as a Ramón y Cajal researcher at BSC. Our work spans molecular to systems-level phenomena: analyzing how energetic landscapes influence protein function and evolution, and extending these concepts to gene regulatory networks and other biological systems. By studying how different constraints and features of biological systems are conserved or co-opted through evolution, the group aims to uncover general principles that govern organization, robustness, evolvability, and designability of life.
The ESBG is looking for a PhD student to work on the Knowledge Generation Project: MEGA-scale Frustration Analysis of the Protein Universe: Evolution, Dynamics, and SNV Impact (MEGAFrustratEDS). The project aims to uncover how local energetic frustration shapes protein evolution, dynamics, and disease-related mutations. Using state-of-the-art structural bioinformatics, machine learning, and high-performance computing, we will build the first Human Proteome-Wide Frustration Atlas — a resource to better classify genetic Single Nucleotide Variants (SNVs) and understand protein function.

The selected student will:

- Integrate this knowledge with evolutionary and clinical variant data to uncover the relationship between local frustration and disease-causing SNVs.
- Contribute to building the Human Proteome-Wide Frustration Atlas & SNV classifier that will be made available to the community.
- PID2024-159128OA-I00

**Key Duties**
- Integration of heterogeneous structural and evolutionary data using advanced data mining techniques
- Analysis of protein conformational ensembles and local energetic frustration
- Contribution to tool development (e.g. FrustraMotion) and creation of the Human Proteome-Wide Frustration Atlas
- Preparation and presentation of scientific articles
- Participation in project meetings and international collaborations

**Requirements**:

- Education
- Undergraduate training in engineering, computer science, physics, mathematics, or other quantitative disciplines is preferred
- MSc in bioinformatics, data science, computational biology, or machine learning-related areas
- Essential Knowledge and Professional Experience
- Previous experience in biophysics, machine learning, statistics, or physics
- Strong programming skills (Python, R; C++ is a plus)
- High motivation and scientific curiosity
- Additional Knowledge and Professional Experience
- Familiarity with structural biology or life sciences research
- Knowledge of AI/ML methodologies
- Experience working with HPC environments
- Fluency in written and spoken English
- Competences
- Good communication and presentation skills
- Ability to work independently and as part of a team

**Conditions**
- 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: 4 years
- Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement
- Starting date: 01/12/2025 or later

**Applications procedure and process**
- A full CV in English including contact details
- A cover/motivation letter with a statement of interest in English, clearly specifying for which specific area and topics the applicant wishes to be considered. Additionally, two references for further contacts must be included. Applications without this document will no