RESEARCHER - EXPLOITATION OF NEXT-GENERATION EARTH SYSTEM OBSERVATION MISSIONS (R3) - 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 Atmospheric Composition (AC) group within the Earth Sciences department at BSC-CNS aims to better understand and predict the spatiotemporal variations of atmospheric pollutants and their effects on air quality, weather, climate, and health.
This mission is achieved through the continuous development and application of numerical models across multiple scales, from weather to climate and from global to urban environments.
The AC group is an international team of approximately 45 members, including researchers, engineers, and students from diverse backgrounds.
A key asset of the AC group is the development and maintenance of MONARCH, a coupled meteorological-chemistry model designed to simulate gaseous chemistry and aerosols, along with their feedback effects on radiation.
MONARCH operates at both global and regional scales, providing operational air quality forecasts for Europe under the Copernicus Atmosphere Monitoring Services (CAMS) and dust forecasts for Africa, the Middle East, and Europe through the Barcelona Dust Regional Center (BDRC).
In addition, daily ensembles of MONARCH forecasts are produced to assimilate ground-based and satellite observations using advanced data assimilation techniques.
These methods are also employed to perform retrospective analyses of atmospheric composition and to estimate aerosol emissions.
We are seeking an experienced researcher to lead the integration of next-generation Earth system observations with the AC group's numerical models, data assimilation techniques, and emerging AI technologies.
This role is pivotal in driving the adoption and integration of AI methodologies to enhance our current forecasting capabilities and fully leverage the potential of new Earth observation data.
The successful candidate would coordinate other researchers, will have access to state-of-the-art systems and computational infrastructures, and will establish collaborations with experts in different areas both at the national and international levels.
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   Consolidate and improve BSC atmospheric composition products (forecasts and reanalyses) Develop and conduct data assimilation experiments with novel satellite products for regional and global air quality Coordinate the transition towards an integrated forecast system capable of assimilating observations of different nature (optical depth at multiple wavelengths, vertical profiles, hyperspectral radiances, in situ observations) Define the strategy for the integration of AI in the current operational data assimilation systems of the AC group Further develop AI knowledge and skills useful to ingest Earth Observations in AC products Lead a small team of researchers and computer engineers Participate in collaborative projects with partner institutions Conduct original research and dissemination in high impact peer reviewed publications, internal and external meetings and conferences.
Provide scientific support for the preparation of competitive applications for research and/or innovation projects   Requirements   Education PhD in the field of atmospheric sciences, environmental sciences, applied mathematics, physics, engineering, or related disciplines.
Essential Knowledge and Professional Experience In-depth knowledge of data assimilation of gases and/or aerosols (6 year minimum) Strong experience with Earth system observations (6 year minimum) Excellent computing skills in high-level computer languages (such as FORTRAN or C), experience with UNIX/LINUX environments and with scripting languages (such as bash) Previous experience coordinating research projects (1 year minimum) Previous experience managing a team of researchers (1 year minimum) Good record in obtaining grants / research funds Additional Knowledge and Professional Experience Fluency in English is essential.
Proficiency in Spanish and other European languages would be advantageous.
Demonstrated experience in machine learning / AI will be valued Experience with revision control systems (e.
., SVN or Git) in large software projects Strong mathematical background is desirable.
Competences Ability to work in a team and in a multi-cultural environment.
Very good interpersonal skills Excellent written and verbal communication skills Ability to take initiative, prioritize and work under set deadlines Ability to work both independently and within a team Capacity to work in multidisciplinary environments   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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