POSTDOCTORAL RESEARCHER - INTEGRATED URBAN AIR QUALITY MODELING: BRIDGING PHYSICS AND DATA SCIENCE (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   At BSC, a postdoc in Integrated Urban Air Quality Modeling focuses on using advanced computational resources for high-resolution simulations of urban air quality.
This involves handling massive datasets and leveraging BSC’s supercomputing capabilities to model pollution at fine spatial and temporal scales.
The role also includes managing uncertainties in these models and applying sophisticated data fusion techniques using machine learning and AI to integrate various data sources and enhance model accuracy.
The mission is to improve urban air quality modeling by conducting high-resolution simulations, quantifying and addressing model uncertainties, and using AI-driven data fusion techniques to integrate sensor measurements.
The goal is to provide actionable insights for urban planners and policymakers to better manage air quality and protect public health.
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   Conduct high-resolution urban air quality modeling through massively parallel simulations.
Perform Uncertainty Quantification to assess and mitigate model uncertainties.
Use data fusion techniques leveraging machine learning and AI algorithms to improve model accuracy by integrating sensor measurements of urban air quality​.
Requirements   Education PhD in Environmental Engineering, Physics, Mathematics, or related fields.
Essential Knowledge and Professional Experience Proficiency in programming languages such as R, Python, C++, Fortran, or Julia.
Experience with numerical models and high-resolution simulations in High-Performance Computing (HPC) environments.
Understanding of Uncertainty Quantification methods.
Additional Knowledge and Professional Experience Fluency in English is essential.
Proficiency in Spanish and other European languages would be advantageous.
Experience with machine learning and artificial intelligence algorithms.
Knowledge of data fusion techniques for urban air quality modeling.
Competences Ability to work in a team and in a multi-cultural environment.
Ability to conduct large-scale, parallel simulations for urban air quality.
Expertise in analyzing uncertainties and improving model outputs using sensor data.
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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