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.
Look at the BSC experience:
BSC-CNS YouTube Channel
Let's stay connected with BSC Folks!
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
In the frame of the AIRE (“Harnessing Artificial Intelligence to TRansform Air Quality AssEssment and Management in Spain”) Spanish national project, in collaboration with CSIC Institute of Environmental Assessment and Water Research and the Univiersity of Zaragoza, the Atmospheric Composition (AC) research group within the Earth Sciences Department (BSC-ES) at the Barcelona Supercomputing Center (BSC) (www.bsc.es) is embarking on a range of cutting-edge research and development activities at the cross-section between environmental sciences (with focus on atmospheric composition and more specifically air pollution) and artificial intelligence.
In this ambitious and potentially rewarding endeavor, we are looking for a machine learning postdoc to develop an emission- and meteorology-sensitive deep learning model emulating the BSC’s in-house MONARCH air pollution model. The AI emulator will be trained on a large ensemble of MONARCH simulations with distinct emission and meteorological forcings. The objective is to build new cost-effective capabilities for air pollution assessment and air pollution planning. The successful candidate will be responsible for this strategic research line, review and monitor the state-of-the-art advances in the field, and coordinate the development of the emulator. A range of cutting-edge architectures (e.g. Transformers, GNN) will be implemented and tested, and their potential/limitations assessed. He/she will consolidate and improve the training/testing pipeline, as well as the postprocessing routines to allow an efficient analysis of the large multidimensional datasets used for training and inferred by the emulator.
See https://www.youtube.com/watch?v=EE8PijwMFXM for a general presentation of our Atmospheric Composition group. In the AC group and BSC-ES department, the successful candidate will have the chance to work in a diverse, international and highly collaborative environment. He/she will have access to the cutting-edge computational resources of Marenostrum 5, one of the largest supercomputer in Europe.
Key Duties
- Review and follow literature on AI-based surrogate models applied to atmospheric models.
- Identify, implement and test different AI architectures for emulating the MONARCH model.
- Develop efficient pre/postprocessing routines for analysing the large atmospheric datasets
- Collaborate with interdisciplinary teams (e.g., atmospheric scientists, data scientists, HPC engineers).
- Publish and present research findings in high-impact scientific journals and conferences.
- Utilize BSC’s high-performance computing resources (e.g., MareNostrum 5) for large-scale AI model training and optimization.
- Document code, workflows, and results following best practices in software development, version control (e.g., Git), and reproducible research.
- Engage in outreach and dissemination activities to promote the project’s objectives and foster collaboration with partners.
Requirements
- Education
- A PhD in environmental engineering, atmospheric sciences, data science, remote sensing, computer science, telecommunications, mathematics or similar.
- Essential Knowledge and Professional Experience
- Excellent computing skills in Python
- Excellent knowledge in deep learning
- Strong experience with Pytorch deep learning framework
- Fluency in English is essential, Spanish is optional (free lessons available after joining)
- Additional Knowledge and Professional Experience
- Experience with UNIX/Linux and HPC environments will be valued
- Experience with Git or similar software version control will be valued
- Experience with coding and documentation best practices and standards
- Experience with parallel programming and/or distributed training across multiple GPUs will be valued
- Experience in atmospheric sciences will be valued
- Experience in developing AI-based surrogate models will be valued
- Competences
- Very good interpersonal skills
- Excellent written and verbal communication skills
- Ability to organize the work, document the advancement and present results
- Ability to take initiative, prioritize and work under set deadlines
- Ability to work both independently and within a team
Conditions
- The position will be located at BSC within the Earth Sciences Department
-
We offer a full-time contract (35h/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: July 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
