Overview
Starting date: 15/02/2026
Job Reference: 9_26_CASE_DT_R3
Job title: MDAO Senior Researcher (part-time) - (R3)
Closing Date: Tuesday, 03 February, 2026
Reference: 9_26_CASE_DT_R3
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.
Context and Mission: The Dual-Use Technologies group is opening a part-time position for a Senior Researcher R3 specialized in Multidisciplinary Analysis Design Optimization (MDAO), and aeroelasticity applied to next-generation aerospace systems. The successful candidate will execute projects integrating multidisciplinary optimization techniques within an HPC environment, leveraging AI techniques, for assisting the design of novel aerospace technologies. This position will be central to advancing our MDAO portfolio within a cutting-edge supercomputing environment, leveraging scalable numerical workflows, automation, and modern computational methods (including data-driven/ML components where appropriate) to enable robust design-space exploration and optimization.
Key Duties
* Design and implement automated pipelines linking parametric model generation to disciplinary solvers including robust pre/post-processing and workflow orchestration.
* Develop and deploy computational methodologies that integrate machine learning / reduced-order modelling with optimization to accelerate design iterations and broaden design-space coverage.
* Develop HPC-friendly strategies for tightly coupled aero-structural/aeroelastic optimization, and integrate them inside the BSC MDAO platform
* Develop/adapt pre-processing (geometric/meshing) kernels for a robust and highly performant integration into MDO workflows
* Actively participate in research dissemination through publications, conferences, and project meetings.
* Mentor junior researchers and contribute to the academic environment of BSC.
Requirements
* Education
o Doctoral degree in Aerospace Engineering or a closely related field, supported by a strong record of research and professional achievements.
o Ph.D. will be considered an added asset.
* Essential Knowledge and Professional Experience
o Demonstrated experience in MDAO/MDO, including multidisciplinary workflow integration and optimization in aerospace contexts.
o Proven expertise in the development of automated pipelines including geometry definition and parametrization, mesh generation and deformation, aerodynamic and structural analysis and optimization.
o Demonstrated experience applying AI/ML to aerospace modelling, including neural-network and data-driven reduced-order aerodynamic models / load estimators used in aeroelastic simulations and preliminary design/MDO contexts (e.g., NN-based loads estimation, NN-ROM aerodynamics, data-driven time-delay models)
o Practical experience supporting aeroelastic analysis and aircraft dynamic response assessment across relevant flight/operational conditions.
o Evidence of research dissemination (peer-reviewed publications and conference participation)
o Programming proficiency in scientific computing workflows (e.g., Python and/or C/C++), and familiarity with standard research software practices (Git, Linux).
* Additional Knowledge and Professional Experience
o Experience interacting with industry and/or institutional programmes in applied aerospace R&D (e.g., collaborative projects, technical support, or contracted activities)
o Familiarity with integrating multiple disciplinary models (e.g., structures with propulsion/aerodynamics and cost models) in a coherent design framework.
o Experience with data-driven modelling / ML for aerospace applications
o Academic engagement (teaching, supervision, laboratory courses)
o Proficiency in Fortran or C/C++ is considered an asset.
o Excellent command of English, both written and spoken.
* Competences
o Ability to take technical ownership of complex workflows and deliver results in collaborative environments.
o Self-criticism and teamwork abilities.
o Curiosity and openness to multidisciplinary aerospace and non-aerospace systems.
Conditions
* The position will be located at BSC within the CASE Department
* We offer a part-time contract (17.5h/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: 22 days of holidays + 6 personal days + 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: 15/02/2026
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@bsc.es. For more information, please follow this link.
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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