Research Engineer In Data Management And Processing

hace 5 días


Barcelona, España Somma A tiempo completo

Reference: 537_24_DIR_CSS_RE3 Job title: Research Engineer in Data Management and Processing (RE3) - AI4S 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, and is a founding member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe).
BSC's mission is to research, develop, and manage information technologies to facilitate scientific progress, combining HPC service provision and R&D under one roof.
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.
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 everyone is appreciated for who they are, regardless of differences.
Context And Mission The Computational Social Science and Humanities Program envisions preparing the social sciences and humanities for the era of data, 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.
We focus on key societal research areas such as Population and Household changes, Democratic Quality, Social Media, Public Opinion, and Political Communication, among others.
As a research engineer and data scientist, you will play a pivotal role in facilitating researchers' work, working closely with the Research units at CSSH and reporting to both the head of the Data Scientists group and the projects' IPs.
The funding for these actions comes from the European Union Recovery and Resilience Facility - Next Generation.
Key Duties Developing workflows for collecting, processing, and curating bibliometric and textual data related to scientific production and policies.
Implementing AI, Machine Learning, Network Analysis, and text classification models.
Ensuring group analyses replicability and data sharing under FAIR conditions.
Developing research tools to advance research in computational social sciences and humanities.
Providing support for adopting researchers' code to High Performance Computing.
Requirements Education Engineering Degree or equivalent.
MSc in Statistics, Computer Science, or similar is highly desirable.
Essential Knowledge and Professional Experience 4 to 10 years of experience curating, managing, and/or analyzing large datasets for research.
Experience with textual data is highly desirable.
Extensive hands-on experience with R and/or Python for data curation and management is essential.
Experience in implementing Machine Learning models and Natural Language Processing technologies is required.
Additional Knowledge and Professional Experience Fluency in English is essential; proficiency in Spanish and other European languages is advantageous.
Experience working with data for social science purposes is preferred.
Competences Interest and ability for independent learning, good communication skills, and ability to work in a team and multi-cultural environment.
Conditions The position will be located at BSC within the Computational Social Science Program.
We offer a full-time contract (37.5h/week), a good working environment, flexible working hours, and a salary of 50.000,00€ with additional expenses grants.
Applications procedure and process All applications must be submitted via the BSC website and contain a full CV in English and a cover/motivation letter.
Applications without these documents will not be considered.
Development of the recruitment process The selection will be carried out through a competitive examination system.
The recruitment process consists of curriculum analysis and an interview phase.
The recruitment panel will ensure at least 25% representation of women.
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