Offer Description
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.
The BSC experience can be found on the BSC-CNS YouTube Channel. We are particularly interested in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research. 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.
If you consider that you do not meet all the requirements, we encourage you to continue applying for the job offer. We value diversity of experiences and skills, and you could bring unique perspectives to our team.
Context And Mission
The Evolutionary Systems Biophysics Group (ESBG) investigates how biological function emerges from physical constraints and evolutionary pressures, across multiple scales — from proteins to regulatory networks. The group combines principles from statistical physics, systems biology, and computational modeling to explore how different abstractions of network dynamics shape biological complexity and adaptability.
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 apply computational techniques to understand the biophysical properties of the native state of proteins and how they explore different conformational substates, integrate this knowledge with evolutionary and clinical variant data to uncover the relationship between local frustration and disease-causing SNVs, and contribute to building the Human Proteome-Wide Frustration Atlas & SNV classifier that will be made available to the community.
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 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. Candidates with a biology background who have significant exposure to quantitative/computational science will also be considered. 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.
* 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: 01/12/2025 or later.
Applications procedure and process
* All applications must be submitted via the BSC website and contain 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.
Development of the recruitment process
The selection will be carried out through a competitive examination system. The recruitment process consists of two phases: Curriculum Analysis and Interview phase.
Curriculum Analysis: Evaluation of previous experience and/or scientific history, degree, training, and other professional information relevant to the position.
Interview phase: The highest-rated candidates at the curriculum level will be invited to the interview phase, conducted by the corresponding department and Human Resources.
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.
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