POSTDOCTORAL RESEARCHER IN ARTIFICIAL INTELLIGENCE APPLIED TO CLIMATE SERVICES (R2) - 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, 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 staff from 60 countries.
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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   The role of the postdoc in Artificial Intelligence applied to Climate Services takes place in a rapidly evolving field where the integration of AI and machine learning is transforming how climate data is processed, analyzed, and applied.
This position is situated within a research group focused on developing cutting-edge methods for climate model calibration, validation, and predictive skill enhancement.
The postdoc will contribute to the ongoing efforts to improve climate services by utilizing explainable AI techniques and integrating them into the BSC (Barcelona Supercomputing Center) ecosystem, which supports environmental and climate research.
The primary mission of the postdoc is to apply explainable machine learning techniques to improve the calibration and validation of climate models.
By identifying windows of opportunity for increasing predictive skill, the postdoc will help optimize the accuracy of climate forecasts and provide actionable insights for stakeholders.
A key aspect of the role involves supporting the development of new software solutions within the BSC ecosystem, enhancing model validation, and streamlining climate prediction methods.
The postdoc will also contribute to advancing research in the field by documenting and publishing their work, fostering collaboration with multidisciplinary teams, and pushing the boundaries of climate services with the integration of AI.
The funding for these actions/fellowships and contracts comes from the European Union Recovery and Resilience Facility - Next Generation, within the framework of the General Invitation by the public business entity Red.
s to participate in the talent attraction and retention programs within Investment 4 of Component 19 of the Recovery, Transformation, and Resilience Plan.
For more information, please check.
https://www.
sc.
s/join-us/excellence-career-opportunities/ai4s     Key Duties   Apply explainable Machine Learning to local and non-local calibration methods for climate models.
Identify windows of opportunity for increased predictive skill using Machine Learning.
Support the development, testing, streamlining, and documentation of new code within the BSC software ecosystem for model validation, calibration, and forecast verification.
Requirements   Education PhD in Climate Sciences, Environmental Sciences, Physics, Mathematics, or related fields.
Essential Knowledge and Professional Experience Proficiency in object-oriented programming, preferably in R or Python.
Understanding of Explainable Machine Learning and its applications in climate models.
Familiarity with calibration methods (local and non-local) and forecast verification.
Additional Knowledge and Professional Experience Fluency in English is essential.
Proficiency in Spanish and other European languages would be advantageous.
Experience in High-Performance Computing (HPC) environments (preferred, but not required).
Knowledge of predictive skill evaluation techniques in climate models.
Competences Ability to work in a team and in a multi-cultural environment.
Ability to explain and interpret Machine Learning models in the context of climate services.
Skills in developing, testing, and documenting code within a collaborative software ecosystem.
Strong communication skills for collaboration with multidisciplinary teams​.
Conditions   The position will be located at BSC within the Earth Sciences Department We offer a full-time contract (37.
h/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 Duration.
4 years Holidays.
23 paid vacation days plus 24th and 31st of December per our collective agreement Salary.
€ Additional Expenses Grant.
Each fellowship will be associated with a grant for additional expenses, such as IT equipment, travel, training, stays, etc.
Starting date.
asap - the incorporation for this vacancy must be before the 16th of 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 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.
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