RESEARCHER - MACHINE LEARNING MODELS FOR THE PREDICTION OF PHYSICOCHEMICAL PROPERTIES OF SUSTAINABLE TRANSPORTATION 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 the transportation sector, despite most propulsion technologies still rely on fossil fuel combustion.
Among the different solutions proposed to alleviate the impact of fossil fuel combustion and move towards the decarbonization of transport and energy sectors, common fuel mixtures are generally blended with oxygenate additives in order to improve properties of conventional hydrocarbon fuels and contribute to a more sustainable transportation market.
For instance, gasoline oxygenated blends generally show improved performance with respect to common gasoline mixtures in terms of combustion and emissions characteristics, by burning leaner and reducing the emissions.
The additives however impact fuel physicochemical properties like distillation curve, vapor pressure, freezing point and octane numbers.
For instance, ethanol is known as an octane number enhancer and has proven to reduce combustion emissions.
Concurrently, the increased use of Artificial Intelligence (AI) and Machine Learn-ing (ML) methods observed in recent years in the combustion community, can be exploited to minimize produc-tion of costly simulations and allow exploration of large data.
ML models have already found application in the prediction of injection spray angles of jets in aviation engines and of physico-chemical properties of fuel and blends of practical interest in the aviation industry.
Within this context, the applicant will lead the development and implementation of a ML algorithm for the pre-diction of fuel mixture properties.
The developed tool aims at efficiently predicting fuel properties for common gasoline-oxygenated fuels and kerosene mixtures, combining experimental databases with thermodynamic laws.
Effect of blends and blending ratios on physico-chemical properties like cetane number, flash boiling or freezing point will be examined by parametrically varying the values of the mentioned quantities in a range of interest.
The activity seeks at boosting use of AI and ML models in combustion problems.
The applicant will join the Pro-pulsion Technologies Group (PTG), a research group from the Computer Applications in Science and Engineer-ing (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 sys-tems.
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.
Key Duties Collaborate with the different partners of the projects to carry our collaborative research.
Leading the development and implementation of AI/ML methods for the calculation of fuel properties Define the input/output structure of the proposed network and of the associated database Identify physical laws and correlations for the mentioned target properties Requirements Education The candidate should hold a PhD Degree in Computer Science, Physics, Mechanical Engineering, or Aerospace.
A solid background in data-driven methods and Artificial Intelligence is required.
Essential Knowledge and Professional Experience Knowledge of fluid mechanics and thermodynamics are expected.
Additional Knowledge and Professional Experience General knowledge on computer science and programming languages such as Fortran, Python, C, and C++ will be considered an asset.
Fluency in English is essential, Spanish is welcome.
Background in computer science, GPU programming and HPC with specific focus on Python programming will be considered an asset.
Competences Strong analytical skills.
Ability to work independently and within a team.
Good communication and team-work skills to work in a multidisciplinary 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, support to the relocation procedures Duration.
Open-ended contract due to technical and scientific activities linked to the project and budget duration Holidays.
23 paid vacation days plus 24th and 31st of December per our collective agreement Salary.
we offer a competitive salary commensurate with the qualifications and experience of the candidate and according to the cost of living in Barcelona Starting date.
Applications procedure and process All applications must be made through BSC website and contain.
A full CV in English including contact details A Cover Letter with a statement of interest in English, including two contacts for further references - Applications without this document will not be considered In accordance with the OTM-R principles, a gender-balanced recruitment panel is formed for every vacancy at the beginning of the process.
After reviewing the content of the applications, the panel will start the interviews, with at least one technical and one administrative interview.
A profile questionnaire as well as a technical exercise may be required during the process.
The panel will make a final decision and all candidates who had contacts with them will receive a feedback with details on the acceptance or rejection of their profile.
At BSC we are seeking continuous improvement in our recruitment processes, for any suggestions or feedback/complaints about our Recruitment Processes, please contact recruitment [at] bsc [dot] es.
For more information 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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