Job Reference: 137_26_ES_AC_RE2
Position: Research support engineer - Atmospheric composition data curation (RE2)
Closing Date: Wednesday, 01 April 2026
Start Date: 01 May 2026
About BSC
The Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC-CNS) is Spain’s leading supercomputing hub, home to MareNostrum, one of Europe’s most powerful supercomputers. BSC is a founding and hosting member of the former PRACE infrastructure, and hosts EuroHPC JU. It conducts research, development, and management of information technologies to facilitate scientific progress, merging HPC services and R&D; across computer and computational science, life, earth, and engineering sciences. The center employs over 1,000 staff from 60 countries.
Context and Mission
The Atmospheric Composition (AC) group within BSC’s Earth Sciences Department focuses on understanding and predicting spatial–temporal variations of atmospheric pollutants and their effects on air quality, weather, and climate. The group develops and operates the MONARCH model (Multiscale Online Non-hydrostatic Atmospheric Chemistry), incorporating advanced chemistry and aerosol packages, and couples it with an aerosol and gas data assimilation system based on the Local Ensemble Transform Kalman Filter. MONARCH contributes to operational dust forecasting at the WMO Regional Specialized Meteorological Center for Atmospheric Sand and Dust Forecast (BDFC) and supports global forecasting efforts through Copernicus and other international programs.
Key Duties
- Data curation of observational datasets, model reanalysis products, and experiment results.
- Apply existing solutions or develop automated procedures to detect missing files, variables, layers, timeframes, or corrupted data.
- Analyze datasets using computed standardized diagnostics.
- Coordinate the development of software packages for satellite observation processing.
- Support researchers in executing and monitoring complex model experiments (ensemble data assimilation runs).
- Collaborate closely with research engineers of the Department to integrate in-house solutions into the data curation process.
- Interact with atmospheric composition scientists to understand and respond to their needs.
Requirements
Education:
- MSc degree in physical sciences, mathematics, or engineering (e.g., Chemistry, Meteorology, Physics, Mathematics, Environmental Engineering, Chemical Engineering).
Essential knowledge and experience:
- 3–5 years of experience in data manipulation and analysis.
- 3–5 years programming in Python, Fortran, and R.
- 3–5 years experience with UNIX/Linux environments.
- Knowledge of Earth Modelling file types (NetCDF, HDF5, GRIB) is valued.
- Experience in similar fields is valued.
Additional knowledge and experience:
- Fluent in English, written and spoken.
Competences:
- Capability to interact with both atmospheric composition and computer scientists.
- Strong initiative, prioritisation, and ability to meet deadlines.
- Independent and team-oriented working style.
Conditions
- Position located at BSC within the Earth Sciences Department.
- Full-time contract (37.5 h/week) with versátil hours, extensive training, restaurant tickets, private health insurance, and relocation support.
- Open-ended contract duration tied to technical activities and budget.
- Holidays: 22 days + 6 personal days + public holidays on 24 & 31 December.
- Competitive salary commensurate with qualifications and cost of living in Barcelona.
- Starting date: 01 May 2026
Application Procedure
All applications must be submitted via the BSC website and include: (1) a full CV in English with contact details; (2) a cover letter (statement of interest) in English; and (3) two references for further contact. Applications missing any of these documents will not be considered.
EEO Statement
BSC-CNS is an equal opportunity employer committed to diversity and inclusion. We welcome all qualified applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected characteristic.
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