Job Reference
734_24_DIR_CSS_RE2
Position
Data scientist for Computational Social Sciences and Humanities (RE2) - AI4S
Closing Date
Thursday, 31 October, 2024
Reference: 734_24_DIR_CSS_RE2
Job title: Data scientist for Computational Social Sciences and Humanities (RE2) - AI4S
About BSC
The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses Mare Nostrum, 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 Euro HPC 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.
Look at the BSC experience:
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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
The Computational Social Science program envisions preparing the social sciences and humanities for the era of data, artificial intelligence (AI), and Exascale supercomputing. Our mission is to foster collaboration between social scientists and computer scientists, making high-performance computing (HPC) accessible to all researchers in the field. Through innovative approaches, we aim to apply social science research to contribute valuable insights for informed policymaking. In our pursuit, we focus on a wide range of key societal research areas such as Population changes and living arrangements, Democratic Quality, Social Media and Information Environment, Social-Ecology, Education and Labor Market, Law technologies, Social Innovation, and History and Cultural Heritage. Employing a mix of complex statistical models, AI/Machine Learning, Large Language Models (LLMs), Agent-Based Modeling (ABM), Social Network Analysis (SNA), among others, our advanced computational methods are applied to diverse datasets from official statistics, surveys, social media, news, laws, historical archives, current data archives, citizens' volunteered data, government and industry data.
You will play a pivotal role in facilitating the researchers' work, collaborating closely with the Research units at CSSH, particularly with the Social Media and Political Communication research areas. You will be part of the Data and Methods for HPCSSH group and report to its director.
The funding for these actions/fellowships and contracts comes from the European Union Recovery and Resilience Facility - Next Generation, within the framework of the General Invitation by the public business entity Red.es to participate in the talent attraction and retention programs within Investment 4 of Component 19 of the Recovery, Transformation, and Resilience Plan.
For more information, please check: https://www.bsc.es/join-us/excellence-career-opportunities/ai4s
"La financiación de estas actuaciones/becas y contratos, procede del Mecanismo de Recuperación y Resiliencia de la Unión Europea-Next Generation, en el marco de la Invitación General de la entidad pública empresarial Red.es para participar en los programas de atracción y retención del talento dentro de la Inversión 4 del Componente 19 del Plan de Recuperación, Transformación y Resiliencia.
Para más información: https://www.bsc.es/join-us/excellence-career-opportunities/ai4s "
Key Duties
- Providing support with text analysis
- Providing support with LLMs and other ML models for multi-modal classification
- Providing support with development of research tools to help researchers carry out their tasks, including data visualization tools
Requirements
- Education
- MA in an area related to Computational Social Sciences or Humanities.
- Essential Knowledge and Professional Experience
- Good programming skills with Python and R
- Experience with topic modeling, clustering models, and LLMs for classification.
- Experience with data sets annotation for model training
- Additional Knowledge and Professional Experience
- Fluency in English is essential. Proficiency in Spanish and other European languages would be advantageous.
- Specific experience in language communication and social media analysis is desired
- Competences
- Ability to work in a team and in a multi-cultural environment.
- Good communication skills for effective collaboration.
- Ability to work both independently and with a team
- Hard-working and highly organized.
Conditions
- The position will be located at BSC within the Computational Social Sciences and Humanities Program.
- 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
- Duration: 4 years
- Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement
- Salary: RE2 42.000,00
- Additional Expenses Grant: Each fellowship will be associated with a grant for additional expenses, such as IT equipment, travel, training, stays, etc.
- Starting date: asap - the incorporation for this vacancy must be before the 16th of December 2024
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.
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