Job Reference
575_24_CASE_PTG_RE1
Position
Research Engineer - Advaned methodologies for combustion simulations (RE1)
Closing Date
Saturday, 31 August, 2024
Reference: 575_24_CASE_PTG_RE1
Job title: Research Engineer - Advaned methodologies for combustion simulations (RE1)
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
Simulation of combustion systems on real applications for gas-turbines is an exceptionally computationally demanding problem. Access to cutting-edge supercomputers opens new frontiers in combustion simulation and encourages a revision of models and methodologies to harness upcoming Exascale machines' full potential. Exascale computing opens new frontiers for the simulation of combustion systems as more realistic conditions can be achieved with high-fidelity methods. However, an efficient use of these computing architectures requires methodologies that can exploit all levels of parallelism.
This Ph. D. position will be focused on the development of an efficient computational framework to conduct high-fidelity simulations of reacting flows for practical applications. The work will address the issue of memory management in flamelet methods, and optimization of algorithms using load balancing techniques to achieve high scalability on large number of computing nodes. The target architectures will include a variety of systems including heterogeneous architectures based on accelerators like GPUs. This PhD constitutes a combined effort between the development of numerical algorithms, its implementation, and the verification of the numerical accuracy and parallel efficiency, for the advancement on high-fidelity large-scale simulations of reacting flows at engine-relevant conditions.
The research team that the applicant will be involved is the Propulsion Technologies Group at CASE Department of BSC. The team is a multidisciplinary group with researchers from all disciplines and with strong background in Computational Fluid Dynamics (CFD). The team is involved in many EU and industrial projects related to this topic, where the successful activities and the publications on highly ranked scientific journals given the proved expertise.
This PhD project fits in the PTG’s recent efforts on the development of advanced computational methods for turbulent combustion modelling, with the aim of reducing the computational cost and complexity of high-fidelity numerical simulations and exploiting the large amount of data generated by simulations and measurements alike. Besides, the algorithmic part, machine learning frameworks will be explored to help identifying relevant physical phenomena, and to provide closure models for large-eddy simulation.
This Ph. D. position will be focused on the development of an efficient computational framework to conduct high-fidelity simulations of reacting flows for practical applications. The work will address the issue of memory management in flamelet methods, and optimization of algorithms using load balancing techniques to achieve high scalability on large number of computing nodes. The target architectures will include a variety of systems including heterogeneous architectures based on accelerators like GPUs. This PhD constitutes a combined effort between the development of numerical algorithms, its implementation, and the verification of the numerical accuracy and parallel efficiency, for the advancement on high-fidelity large-scale simulations of reacting flows at engine-relevant conditions.
The research team that the applicant will be involved is the Propulsion Technologies Group at CASE Department of BSC. The team is a multidisciplinary group with researchers from all disciplines and with strong background in Computational Fluid Dynamics (CFD). The team is involved in many EU and industrial projects related to this topic, where the successful activities and the publications on highly ranked scientific journals given the proved expertise.
This PhD project fits in the PTG’s recent efforts on the development of advanced computational methods for turbulent combustion modelling, with the aim of reducing the computational cost and complexity of high-fidelity numerical simulations and exploiting the large amount of data generated by simulations and measurements alike. Besides, the algorithmic part, machine learning frameworks will be explored to help identifying relevant physical phenomena, and to provide closure models for large-eddy simulation.
Key Duties
- The main duties include the development of advanced algorithms for high-fidelity combustion simulations using MPI and GPU-accelerated solutions for supercomputers. It also includes the development of an efficient computational framework to train and assess convolution neural networks (CNN) on highly resolved CFD data. The created models will be used to identify complex physical phenomena, and to develop subgrid closures for turbulent combustion modelling.
Requirements
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Education
- MSc Degree in Chemistry, Physics, Mechanical Engineering, or Aerospace.
- The candidate should fulfill the requirements to be enrolled in the Computational and Applied Physics PhD Program (https://doctorat-fcia.postgrau.upc.edu/en/academic-information/admission-to-the-doctoral-programme) from the Universitat Politècnica de Catalunya.
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Essential Knowledge and Professional Experience
- General knowledge on fluid mechanics, chemistry, thermodynamics, numerical methods are expected.
- Advanced knowledge of python and machine learning models is welcome.
- Background in fluid mechanics and thermal systems.
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Additional Knowledge and Professional Experience
- Computational skills and parallel programming for HPC are not necessary, but will be considered an asset.
- Solid background on fluid mechanics will be positively evaluated.
- Fluency in English is essential, Spanish is welcome.
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Competences
- Ability to work independently and make decisions.
- 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 (37.5h/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, 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: 16/09/2024
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
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.
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