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Job Reference

724_25_ES_ACA_RE2

Position

Research Engineer to support the development of AI models for scientific applications in atmospheric chemistry (RE2)

Closing Date

Friday, 12 December, 2025

Reference:
724_25_ES_ACA_RE2

Job title:
Research Engineer to support the development of AI models for scientific applications in atmospheric chemistry (RE2)

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
We are seeking a motivated Research Engineer to join the Atmospheric Composition (AC) group in the Earth Sciences Department at BSC-CNS. The AC group (~50 researchers: engineers, predocs, postdocs, and senior scientists) develops and applies numerical models to understand and predict atmospheric pollutants and their interactions with weather and climate. The group builds and maintains the MONARCH model, a state-of-the-art atmospheric composition system used for research and operations, including within the Copernicus Atmospheric Monitoring Service (CAMS).

As the group accelerates its use of machine learning for air quality and atmospheric chemistry, we are looking for a Research Engineer who will provide technical and scientific support for the development, optimization, and deployment of AI models, with a strong focus on PyTorch, distributed training, and HPC integration.

The successful candidate will work closely with scientists developing AI-based emulators, downscaling models, inverse modeling systems, and hybrid ML–numerical modeling workflows. The position involves optimizing model training on MareNostrum 5's GPU-accelerated partition, enabling scalable workflows, and supporting codebases that integrate Python, PyTorch, and Fortran components.

You will be embedded in a dynamic team working at the frontier of atmospheric research, scientific machine learning, and high-performance computing.

Key Duties

• Support the development, debugging, and optimization of deep learning models for atmospheric chemistry and air quality applications.
• Implement and maintain distributed training pipelines using PyTorch, NCCL, and HPC job schedulers (e.g., SLURM).
• Collaborate on adapting ML models for large-scale GPU systems (multi-GPU, multi-node).
• Assist in integrating AI components with existing Fortran-based numerical models (e.g., MONARCH-CAMP).
• Develop robust and efficient Python workflows for training, evaluation, and operational deployment.
• Contribute to code optimization, refactoring, and parallelization strategies across heterogeneous architectures.
• Work closely with atmospheric scientists and software engineers to integrate AI workflows into the group's modeling ecosystem.
• Document tools and workflows, provide support to team members, and contribute to group meetings and presentations.

Requirements

• Education

• MSc or BSc with strong experience in Computer Science, Earth Sciences, Applied Mathematics, Physics, or related fields.

• Essential Knowledge and Professional Experience

• Strong background in deep learning, preferably with PyTorch.

• Proven experience with HPC environments, including GPU clusters and job schedulers.
• Expertise in distributed training (DDP, data parallelism, mixed precision).
• Excellent programming skills in Python.

• Demonstrated ability to develop and maintain scientific or machine learning software.

• Additional Knowledge and Professional Experience

• Experience using and interfacing with Fortran codebases.

• Familiarity with atmospheric science or numerical modeling environments.
• Experience with code profiling and performance optimization tools.
• Experience with version control systems (Git).

• Experience with containerization (Docker, Singularity) and reproducible workflows is a plus.

• Competences

• Ability to work both independently and as part of a collaborative team.

• Strong communication skills and fluency in English (written and verbal).
• Good organization, initiative, and ability to prioritize tasks.
• Problem-solving mindset and willingness to support scientific users.

Conditions

• The position will be located at BSC within the Earth 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: Open-ended contract due to technical and scientific activities linked to the project and budget duration
• 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: december

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

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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