POSTDOCTORAL RESEARCHER- AI/ML-ASSISTED ANALYSIS OF SPRAY FLAME COMBUSTION FOR AVIATION FUELS (R2)

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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Context And Mission   Nowadays considerable effort is put on making renewable energies a practical technology in aircraft engines, despite most propulsion technologies employed within the transportation sector still rely on fossil fuel combustion.
As so, modelling of reacting two-phase flows remains a fundamental task to help design more efficient engines and reduce emissions.
The increased use of Artificial Intelligence (AI) and Machine Learning (ML) methods in combustion observed in recent years can be exploited to minimize production of costly simulations and at the same time allow exploration of large data from already available ones.
ML models have in fact been employed to predict injection spray angles of jets in aviation engines and physico-chemical properties of fuel and blends of practical interest in the aviation industry.
Moreover, optimization algorithms can be used to derive fuel surrogates which mimic chemical or physical properties of the original ones, which generally consist of thousands of species, thus requiring large and detailed kinetic mechanism for their numerical analysis.
Specifically in the emerging and still relatively unexplored field of Sustainable Aviation Fuel (SAF), these tools could be of great help to get fundamental insights on how these fuels burn or how their properties change based on the feedstock and the fuel pathway considered.
This is particularly true given the current lack of experimental data on these newly proposed fuels.
Within this context, the applicant will lead the development and implementation of ML-models for high-fidelity spray flame simulations.
Research activities will be carried out in the framework of the project AI4S funded to develop ML-based models for the simulation of reacting sprays.
The activity inherits the research group expertise collected during the EU CoEC project (https://coec-project.
u) and seeks at boosting use of AI and ML models in spray combustion with SAF.
The applicant will join the Propulsion Technologies Group (PTG), a research group from the Computer Applications in Science and Engineering (CASE) Department at the Barcelona Supercomputing Center.
As part of the PTG, the applicant will form part of a multidisciplinary team of researchers with a strong background on Computational Fluid Dynamics (CFD) applied to high-fidelity simulations for the development of clean propulsion and power generation systems.
The PTG is actively involved in several European research-oriented and industrial projects for which results are disseminated in highly ranked scientific journals and conferences.
The applicant is expected to lead fundamental analysis on multicomponent evaporation of realistic fuels for spray flame simulations and boost the use of AI methods for the prediction of fuel behavior, from injection and evaporation up to combustion modes and emissions.
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   Leading the development and implementation of AI/ML methods in Python and Fortran environments for SAF combustion, with particular focus on fuel properties determination, fuel surrogate definition and emissions predictions Perform high fidelity simulations of spray flame combustion to build high fidelity databases for SAF combustion.
Contribute to scientific publications and reporting to different National and EU projects the researcher will be involved in.
Supervision of PhD students and MSc students from the group.
Requirements   Education The candidate should hold a PhD Degree in Computer Science, Physics, Mechanical Engineering, or Aerospace.
Background in combustion and thermal systems will be considered an asset.
Essential Knowledge and Professional Experience Knowledge of fluid mechanics, multi-phase flows, and thermodynamics are expected.
Advanced knowledge of spray modelling is also expected.
Additional Knowledge and Professional Experience Fluency in English is essential.
Proficiency in Spanish and other European languages would be advantageous.
General knowledge on computer science, HPC, and programming languages such as Fortran, Python, C, and C++ will be considered an asset.
Competences Ability to work in a team and in a multi-cultural environment.
Strong analytical skills.
Ability to work independently and within a team.
Conditions   The position will be located at BSC within the CASE 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.
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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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