Research Engineer – Event Monitor Analysis (RE1)

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AI Summary

Research and develop Event Monitor Multiplexing methodologies for real-time AI-based frameworks. Focus on improving data extraction, modeling, and validation of complex event profiles. Requires a degree in Mathematics, Computer Science, or Statistics with practical experience in Event Monitor Analysis.

Key Highlights
Research and develop Event Monitor Multiplexing methodologies for real-time AI-based frameworks.
Improve data extraction, modeling, and validation of complex multivariate event profiles.
Contribute to academic publications and propose new methodologies.
Key Responsibilities
Contribute to the research of Event Monitor Multiplexing techniques to improve data gathering of AI-based control applications in real-time edge devices.
Develop data gathering techniques and tools to enable Topological Data Analysis on complex high-performant hardware in critical systems for software specification, design, implementation, verification and validation, and the disruptive and innovative nature of deep learning software.
Technical Skills Required
Event Monitor Analysis Topological Data Analysis Machine Learning
Benefits & Perks
Full-time contract (35h/week)
Flexible working hours
Extensive training plan
Restaurant tickets
Private health insurance
Support to relocation procedures
Nice to Have
Knowledge of safety-critical systems
Experience with data science techniques

Job Description


Job Reference

313_26_CS_SDES_RE1

Position

Research Engineer – Event Monitor Analysis (RE1)

Closing Date

Tuesday, 07 July, 2026

Reference: 313_26_CS_SDES_RE1

Job title: Research Engineer – Event Monitor Analysis (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.

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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 High-Performance Embedded Systems (HPES) laboratory aims at enabling the adoption of hardware, software, and artificial intelligent (AI) HPC solutions in embedded systems as its center of gravity, but also in any system with some form of criticality like cars, airplanes and satellites. Our work is mainly done in the context of bilateral projects with several processor companies as well as several European-funded projects. For a complete list of publications of the group in the last years, please visit this link.

The objective of this position is to work in the context of several European and bilateral Projects on high-performance real-time AI-based frameworks as part of a young and dynamic team researching on computer architecture (processors and accelerators), operating system support, and statistical and AI frameworks.

In particular, the candidate will research and develop Event Monitor Multiplexing methodologies focused on improving data extraction of real-time AI-based frameworks. The current challenges involve dealing with complex multivariate event profiles that require complex modelling and validation. Furthermore, the candidate will work on data gathering methodologies that enable the proper use of Topological Data Analysis techniques. The candidate will also work on helping develop academic publications. The candidate will be expected to propose new methodologies based on those challenges and/or improve the state-of-the-art.

The candidate is expected to have conducted his/her studies on related topics to real-time, Topological Data Analysis, AI or statistical techniques. Experience is welcome but not mandatory. The candidate will join a team of several people helping him/her to familiarize with the needed tools and developments for a smooth ramp up process. This position offers the possibility to collaborate with research institutions and industry from several European locations, thus offering enriching experiences and opportunities to learn

Key Duties

  • Contribute to the research of Event Monitor Multiplexing techniques to improve data gathering of AI-based control applications in real-time edge devices
  • Develop data gathering techniques and tools to enable Topological Data Analysis on complex high-performant hardware in critical systems for software specification, design, implementation, verification and validation, and the disruptive and innovative nature of deep learning software

Requirements

  • Education
    • Degree in Mathematics, Computer Science or Statistics
  • Essential Knowledge and Professional Experience
    • Practical experience on Event Monitor Analysis
    • Some practical experience in data management and data augmentation.
    • Knowledge of Topological Data Analysis
    • Familiarity with machine learning algorithms
  • Additional Knowledge and Professional Experience
    • Knowledge of safety-critical systems
    • Experience with data science techniques is also welcome
  • Competences
    • Problem-solving, pro-active, result-oriented work attitude
    • Good communication skills including a good command of the English language (written and spoken)
Conditions

  • The position will be located at BSC within the Computer Sciences Department
  • We offer a full-time contract (35h/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: 21/07/2026

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.

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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