Job Reference
588_24_ES_AC_R3
Position
Researcher - Understanding air pollution patterns, trends and impacts (R3) - AI4S
Data de tancament
Dimarts, 03 Setembre, 2024
Reference: 588_24_ES_AC_R3
Job title: Researcher - Understanding air pollution patterns, trends and impacts (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 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.
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
The Atmospheric Composition (AC) group within the Earth Sciences department at BSC-CNS aims at better understanding and predicting the spatiotemporal variations of atmospheric pollutants along with their effects upon air quality, weather, climate and health. This is addressed through the continuous development and application of numerical models over multiple scales, from weather to climate and from global to urban scales. The AC group is an international team of approximately 45 members, including researchers, engineers, and students from diverse backgrounds.
Air pollution is inherently dynamic, with levels that fluctuate based on season, time of day, long-term trends, meteorological conditions, and the effects of climate change. Different pollutants interact uniquely with these factors, leading to diverse and complex patterns in air quality. By deepening our understanding of these variations, we can more effectively design policies and actions that target the periods and conditions of the most severe air pollution.
The AC group manages a comprehensive storage system of Earth system observations, both in-situ and satellite-based, which supports air quality model evaluation, process analysis, and data assimilation. This system is meticulously curated using harmonization and standardized processing methodologies to ensure the highest quality of data.
We are seeking an experienced researcher to join the AC group and lead innovative research focused on air pollution patterns, trends, and impacts. The successful candidate will spearhead the integration of advanced AI methodologies for the curation, analysis and fusion of observational data and atmospheric chemistry model datasets. These AI-driven approaches will enable the identification of patterns and trends that traditional methods may overlook, providing new insights into air quality dynamics.
The successful candidate will have access to state-of-the-art systems and computational infrastructures and will be part of a vibrant and collaborative research environment.
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.es 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.bsc.es/join-us/excellence-career-opportunities/ai4s
Air pollution is inherently dynamic, with levels that fluctuate based on season, time of day, long-term trends, meteorological conditions, and the effects of climate change. Different pollutants interact uniquely with these factors, leading to diverse and complex patterns in air quality. By deepening our understanding of these variations, we can more effectively design policies and actions that target the periods and conditions of the most severe air pollution.
The AC group manages a comprehensive storage system of Earth system observations, both in-situ and satellite-based, which supports air quality model evaluation, process analysis, and data assimilation. This system is meticulously curated using harmonization and standardized processing methodologies to ensure the highest quality of data.
We are seeking an experienced researcher to join the AC group and lead innovative research focused on air pollution patterns, trends, and impacts. The successful candidate will spearhead the integration of advanced AI methodologies for the curation, analysis and fusion of observational data and atmospheric chemistry model datasets. These AI-driven approaches will enable the identification of patterns and trends that traditional methods may overlook, providing new insights into air quality dynamics.
The successful candidate will have access to state-of-the-art systems and computational infrastructures and will be part of a vibrant and collaborative research environment.
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.es 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.bsc.es/join-us/excellence-career-opportunities/ai4s
Key Duties
- Definition of the strategy of the AI solutions for atmospheric composition data treatment and analysis
- Further develop and apply AI knowledge and skills
- Advance the understanding of atmospheric chemistry processes
- Develop and apply novel methodologies for data fusion, model evaluation and analysis
- Contribute to the development of the evaluation tools of the group
- Coordinate other researchers or 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 chemistry, environmental sciences, applied mathematics, physics, engineering, or related disciplines.
- Essential Knowledge and Professional Experience
- In-depth knowledge of atmospheric chemistry (6 year minimum)
- Experience with Earth system observations and data treatment (6 year minimum)
- Experience with atmospheric composition (modeling, data assimilation or 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) are required
- Previous experience participating in international research projects (2 year minimum)
- Previous experience coordinating a team of researchers or engineers (1 year minimum)
- Additional Knowledge and Professional Experience
- Fluency in English is essential. Proficiency in Spanish and other European languages would be advantageous.
- Experience in machine learning / AI will be valued
- Knowledge of atmospheric science data formats (GRIB, NetCDF) and previous experience with scientific software and tools (CDO, NCO, Python or R)
- Experience with revision control systems (e.g., SVN or Git)
- 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 (37.5h/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: 55.000,00 €
- 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 2024
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
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