POSTDOC ON AI MODELIZATION FOR EDGE AI SYSTEMS - AI4S (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 staff from 60 countries.
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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 deployment of Artificial Intelligence (AI) based solutions to deliver advanced software functionalities is consolidating as a key competitive factor in several industrial domains.
AI solutions are the cornerstone for enabling autonomous operation and decision making along the computing continuum from large servers to small edge devices.
These systems must process massive amounts of data from multiple sensors, ensuring reliable and safe operations.
The complexity of AI-based software requires robust mathematical modeling to meet Functional Safety (FuSa) standards, which dictate stringent requirements for these systems to deliver explainable and reliable results.
The candidate will devise mathematical models to address FuSa compliance.
The candidate will collaborate intensively in multidisciplinary projects, involving experts in AI to meet FuSa requirements for specific AI use-case scenarios.
Additionally, the candidate will develop algorithmic-level solutions for monitoring and diagnostics of Edge-AI systems’ decisions.
This position aims to work within a small team to develop AI solutions for safety-critical systems on the edge, focusing on the connection between explainability and causality, taking into account the uncertainty in these explanations, and through the use of probabilistic modeling.
These aspects are crucial for meeting FuSa standards by providing transparency, reliability, and predictability in AI systems.
The funding for these actions/fellowships and contracts comes from the European Union Recovery and Resilience Facility - Next Generation, within the framework of the General Invitation by the public business entity Red.
s to participate in the talent attraction and retention programs within Investment 4 of Component 19 of the Recovery, Transformation, and Resilience Plan.
For more information, please check.
https://www.
sc.
s/join-us/excellence-career-opportunities/ai4s     Key Duties   Develop mathematical models for Edge-AI systems focusing on explainability, causality, uncertainty modeling, and probabilistic modeling in AI to enhance the reliability and transparency of AI solutions.
Collaborate with multidisciplinary teams to integrate explainability, causality, and uncertainty modeling techniques into existing AI systems.
Identify FuSa-related metrics and develop mathematical approaches for diagnosis and monitoring based on those metrics.
Lead a small team of junior engineers and students contributing to these tasks.
Requirements   Education Master’s Degree in Computer Science, Mathematics, or similar.
A PhD in the area (or being in the last year of the PhD).
Essential Knowledge and Professional Experience Strong knowledge on AI fundamentals.
Familiarity with Deep Learning frameworks (e.
.
PyTorch, Tensorflow, JAX).
Deep knowledge on Causal Inference fundamentals, particularly on the Causal Graphs perspective.
Experience in collaborative projects.
Strong practical experience in programming languages (Python, C++, etc.) Additional Knowledge and Professional Experience Previous experience in European projects in similar areas.
Previous experience in Data Science projects, particularly for industry applications.
Competences Problem-solving, proactive, collaborative, and result-oriented work attitude Good communication skills including proficiency in English (both written and spoken)   Conditions   The position will be located at BSC within the Computer Sciences Department We offer a full-time contract (37.
h/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 Duration.
4 years Holidays.
23 paid vacation days plus 24th and 31st of December per our collective agreement Salary.
€ Additional Expenses Grant.
Each fellowship will be associated with a grant for additional expenses, such as IT equipment, travel, training, stays, etc.
Starting date.
asap - the incorporation for this vacancy must be before the 16th of December   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 [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.
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