Senior AI for Earth Sciences Team Co-Lead

Job Reference

339_26_ES_CES_R3

Position

Senior AI for Earth Sciences Team Co-Lead (RE3-R3)

Closing Date

Saturday, 08 August, 2026

Reference: 339_26_ES_CES_R3

Job title: Senior AI for Earth Sciences Team Co-Lead (RE3-R3)

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

The mission of the Earth Sciences Department of the Barcelona Supercomputing Centre, led by Prof. Francisco Doblas-Reyes, is to carry out research and develop methods for environmental forecasting, with a particular focus on the atmosphere-ocean-biosphere system. This includes the management and transfer of technology to support key societal challenges through the use of models and data applications in High Performance Computing (HPC) and AI infrastructures. It also includes the dissemination of real-time air quality and climate information based on its research expertise in collaboration with the Spanish authorities and the World Meteorological Organisation (WMO).

The successful candidate will join the Computational Earth Sciences group to co-lead the Artificial Intelligence Team, which is responsible for developing and applying machine learning and AI methods, including deep learning models, emulators, and data-driven techniques, to advance climate and earth system research. The team contributes AI expertise to major EU-funded initiatives, including Climate-DT / Destination Earth, ELLIOT, CONCERTO, TerraDT, EXPECT, among others, translating cutting-edge AI research into tools and services with real scientific and societal impact.

The AI Team plays a growing role in the department's research, bridging fundamental AI research and its application to climate and Earth science challenges. It has strong links with the other teams in the Computational Earth Sciences group and with the research groups across the department.

Key Duties

• Co-lead the coordination and supervision of a team of around 15 research engineers and scientists, alongside the current Team Lead.
• Lead the planning, execution, and completion of ongoing and new AI research and engineering projects within the team, assigning tasks and prioritising them.
• Identify and pursue opportunities to sustain the team's AI models, tools, and funding lines.
• Contribute to the development strategy of the department's AI tools, thereby increasing the applicability and international visibility, and hence impact, of the research arising from current and future projects.
• Contribute to the research activities of the team by identifying potential new lines of research and assisting in the publication and dissemination of the team's research activities.
• Co-lead the AI Team's day-to-day management of tasks and deliverables, and supervise team members, together with the current Team Lead. The candidate will report to the Head of the Computational Earth Sciences Group.
  
  

Requirements

• Education
• Master's degree in Machine Learning, Data Science, Computer Science, Earth Sciences, Environmental Sciences, or a closely related field. A PhD in a related field is not essential but will be appreciated.
• Essential Knowledge and Professional Experience
• Experience applying deep learning and other AI/ML methods to climate or earth science research or applied work.
• Experience in leading or managing a team, including assigning tasks, setting goals, providing feedback, and facilitating collaboration.
• Excellent communication and interpersonal skills to work effectively within interdisciplinary teams and with external stakeholders.
• Additional Knowledge and Professional Experience
• Proven ability to manage large and collaborative projects, including supervision of PhD or Master's students.

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• Proficiency in Python and deep learning frameworks (e.g. PyTorch, TensorFlow/JAX), with experience in UNIX/Linux environments.
• Proven experience in scientific research, particularly in areas related to climate or earth system modelling.
• Familiarity with training and deploying AI models on large HPC systems, including distributed/parallel training approaches.
• Experience working with large-scale scientific or earth observation datasets.
• Familiarity with MLOps and model profiling/optimisation tools.
• Competences
• Proven leadership skills, including the ability to inspire and motivate team members, foster a collaborative and inclusive working environment, and resolve conflict effectively.
• Ability to interact and build strong relationships with colleagues across scientific disciplines, fostering a collaborative research environment.
• Strong organisational skills, including the ability to prioritise tasks, manage resources efficiently and meet deadlines.
• Strategic thinking and problem-solving skills, with the ability to anticipate challenges and develop innovative solutions.
• Proficiency in English, both written and oral. Experience in writing technical reports and/or scientific publications will be appreciated.
  

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: 01/10/2026
  
  

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@bsc.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.

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