PhD Student – Mechanistic Interpretability

hace 5 días


Barcelona, Barcelona, España Barcelona Supercomputing Center (BSC) A tiempo completo
Job Reference

743_25_LS_LT_R1

Position

PhD Student – Mechanistic Interpretability

Closing Date

Thursday, 18 December, 2025

Reference: 743_25_LS_LT_R1

Job title: PhD Student – Mechanistic Interpretability

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 are particularly interested for this role in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research. In instances of equal merit, the incorporation of the under-represented sex will be favoured.

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

"Multilingual Production Principles of Lexical Collocations" (MaPPLexiC) is a project funded by the European Research Council over the next five years 2025 – 2030. Leveraging recent advances in Computational Lexicography, Cognitive Science and Neural Computational Linguistics, MaPPLexiC aims to uncover and articulate in terms of human understandable rules why certain words combine to form idiosyncratic combinations, i.e., collocations, to convey specific meanings by interpreting neural collocation recognition and classification models.

In the context of MaPPLexiC, we are looking for a young, motivated researcher with interest in lexical combinatorics and cognitive approaches to language to pursue their PhD studies in the area of mechanistic interpretability of collocation classification models. The PhD research is expected to explore, among other techniques, probing, covert feature identification and lexicalization, and feature dimension reduction and test them on selected pairs of Germanic, Romance, Slavic and Finno-Ugric languages. The successful candidate will already have solid background knowledge and practical experience in neural Natural Language Processing. The candidate will work under the supervision of an experienced Postdoc researcher and the PI of MaPPLexiC Prof. Leo Wanner.

Key Duties

  • Explore existing methods for mechanistic interpretability and research (design and develop) novel techniques for this task.
  • Contribute to the design and implementation of feature visualization techniques in neural representations.
  • Participate in cross-language evaluation studies.
  • Contribute to the improvement of the performance of existing neural collocation recognition and classification models.
  • Collaborate with the corpus annotation team.

Requirements

  • Education
  • Master in Computational Linguistics, Computer Science, Machine Learning, Mathematics, or Physics.
  • Essential Knowledge and Professional Experience
  • Solid theoretical knowledge in neural language modeling and natural language processing.
  • Strong programming skills in Python and deep learning frameworks
  • Ability to work effectively in a collaborative, multidisciplinary environment
  • Additional Knowledge and Professional Experience
  • Expertise in implementation of deep machine learning-based applications.
  • Competences
  • Fluency in spoken and written English.
  • Competence in one or several languages of the project (Czech, Finnish, French, German, Hungarian, Russian, and Spanish) and any additional language is an advantage.

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: 1 year
  • Holidays: 22 days of holidays + 6 personal days + 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: 01/01/2026

Applications procedure and process

All applications must be submitted via the BSC website and contain:

  • 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 not be considered.

Development of the recruitment process

The selection will be carried out through a competitive examination system ("Concurso-Oposición"). The recruitment process consists of two phases:

  • Curriculum Analysis: Evaluation of previous experience and/or scientific history, degree, training, and other professional information relevant to the position. - 40 points
  • 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. In this phase, technical competencies, knowledge, skills, and professional experience related to the position, as well as the required personal competencies, will be evaluated. - 60 points. A minimum of 30 points out of 60 must be obtained to be eligible for the position.

The recruitment panel will be composed of at least three people, ensuring at least 25% representation of women.

In accordance with OTM-R principles, a gender-balanced recruitment panel is formed for each vacancy at the beginning of the process. After reviewing the content of the applications, the panel will begin the interviews, with at least one technical and one administrative interview. At a minimum, a personality questionnaire as well as a technical exercise will be conducted during the process.

The panel will make a final decision, and all individuals who participated in the interview phase will receive feedback with details on the acceptance or rejection of their profile.

At BSC, we seek continuous improvement in our recruitment processes. For any suggestions or comments/complaints about our recruitment processes, please contact recruitment [at] bsc [dot] es.

For more information, please follow this link.

Deadline

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

OTM-R principles for selection processes

BSC-CNS is committed to the principles of the Code of Conduct for the Recruitment of Researchers of the European Commission and the Open, Transparent and Merit-based Recruitment principles (OTM-R). This is applied for any potential candidate in all our processes, for example by creating gender-balanced recruitment panels and recognizing career breaks etc.

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.

For more information follow this link



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