PhD student

Job Reference

856_24_CASE_LSCFD_R1

Position

PhD student - algorithms for detailed characterization and feature extraction (R1)

Closing Date

Sunday, 30 November, 2025

Reference:
856_24_CASE_LSCFD_R1

Job title:
PhD student - algorithms for detailed characterization and feature extraction (R1)

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.

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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 quest for carbon-neutral aviation propels us toward uncharted technological frontiers. In ERC Synergy TRANSDIFFUSE, we present an ambitious program to develop an AI-driven model that may revolutionize propulsion technologies. As a synergistic consortium, we unite the numerical modelling prowess of UPM team, the high-fidelity computational capabilities of LS/CFD group at BSC, and Purdue University experimental ingenuity.

TRANSDIFFUSE aims to develop new tools related to clean propulsion, specifically an AI-driven model called FluidGPT. In doing so, we expect to enable major advancements to the aeronautical and power generation sectors, including, for example, hydrogen pressure gain combustion (PGC) engines, which are compact, lightweight, high-efficiency turbines. In initiating FluidGPT, we aim to overcome challenges like those facing PGC, by exploiting the thing that has made compact turbomachinery so difficult to design: the troublesome transonic flows propelled from the combustor. With our model we aim to control and manipulate those transonic flows.

TRANSDIFFUSE will unfold in structured phases, beginning with extensive experimental and computational exploration of unsteady transonic turbine phenomena; followed by creation of FluidGPT, informed by the physics captured in Phase I; and last, applying FluidGPT to discover novel flow control strategies and exploit flow instabilities. Most of the tools required to achieve TRANSDIFFUSE are in the early stages of development. We intend to advance or develop theoretical modelling and computational and experimental tools as we progress through the project. Our collaborative endeavour thrives on the dynamic interplay between

computation, modelling, and experimental disciplines, ensuring that insights gleaned from each area amplify the impact and accuracy of the others.

The present PhD proposal is contained in the Phase I researching in algorithms for detailed characterization and feature extraction including development of methods to carry out eigenmode analysis taking advantage of novel GPU platforms.

Key Duties

• To develop feature extraction for massive data sets accelerated by means of GPU
• To assess the developed algorithms in TRANSDIFFUSE basic test cases
• To participate in the rest of the CFD activities of the LS/CFD team in CASE.
• To develop highly scalable eigenmode analysis algorithms

Requirements

• Education

• MSc in computational fluid dynamics

• Essential Knowledge and Professional Experience

• Experience in CFD development ( at least 1 year)

• Knowledge in large eddy simulation models ( at least 1 year)
• Experience in large-scale simulation at high speed (wall models for LES, complex mesh generation, industrial simulations, etc. ) ( at least 1 year)
• Understanding of HPC clusters at a user level and experience programming MPI ( at least 1 year).

• Good programming level (python, C, Fortran, C++, etc.) ( at least 1 year)

• Additional Knowledge and Professional Experience

• Good writing and oral skills (English is a must)

• Competences

• CFD development knowledge

• Experience in large-scale CFD computations (meshing, running in HPC systems and post-processing large data sets)
• Turbulence modelling (LES and RANS modelling, including wall modelling)
• Experience in European projects

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: 1 year
• 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: asap

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

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

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