Job Reference
333_25_CS_HPES_R0
Position
Undergraduate Student - real-time, probabilistic modelling, AI or statistical techniques (R0)
Data de tancament
Dimarts, 13 Maig, 2025
Reference: 333_25_CS_HPES_R0
Job title: Undergraduate Student - real-time, probabilistic modelling, AI or statistical techniques (R0)
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
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 probabilistic and statistical analysis focused on solving the timing challenges of real-time AI-based frameworks. The current challenges involve dealing with graph-like execution time data to build probabilistic models. The candidate will also work on theoretical toy models that simplify the complex hardware which will aid the final modelling on real hardware. 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, probabilistic modelling, 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.
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 probabilistic and statistical analysis focused on solving the timing challenges of real-time AI-based frameworks. The current challenges involve dealing with graph-like execution time data to build probabilistic models. The candidate will also work on theoretical toy models that simplify the complex hardware which will aid the final modelling on real hardware. 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, probabilistic modelling, 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 and application of probabilistic and statistical techniques to modelling aspects of AI-based control applications in real-time edge devices
- Develop probabilistic models for graph-like data and tools to bring insights to the analysis of 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
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Education
- Degree in Mathematics, Applied Statistics, or Physics
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Essential Knowledge and Professional Experience
- Recognized experience in statistical analysis
- Experience with Mathematical Modelling
- Experience with real-time edge AI systems
- Experience with R and Python
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Additional Knowledge and Professional Experience
- Experience in software timing analysis in commercial and academic environments
- Good communication skills including a good command of the English language (written and spoken)
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Competences
- Problem-solving, pro-active, result-oriented work attitude
- Ability to take initiative, prioritize and work under set deadlines pressure
- Ability to work independently and in a team
Conditions
- The position will be located at BSC within the Computer Sciences 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: 01/06/2025
Applications procedure and process
All applications must be submitted via the BSC website and contain:
The selection will be carried out through a competitive examination system ("Concurso-Oposición"). The recruitment process consists of two phases:
- 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 [at] bsc [dot] 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
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