Spain Job Openings
Barcelona Supercomputing Center (BSC)
Research Engineer – Agent-based models for explainability – AI4S (RE2)
Barcelona
FULL TIME
September 16, 2024
Job Reference
Position
Closing Date
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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.
We are currently conducting research on analysing and explaining the behaviour of opaque (non-transparent or black-box) Artificial Intelligence agents, including agents based on reinforcement learning, logic-symbolic formalisms or large language models. The main objective is to produce novel models for the generation of telic explanations that allow research practitioners and end users to understand the behaviour of virtual and physical agents, predict their expected actions and trust their behaviour. The methods to be explored are multidisciplinary, including (but not limited to) formal logics, epistemology, causal theory, computational linguistics and machine learning.
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.es 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.bsc.es/join-us/excellence-career-opportunities/ai4s
- Do research in the field of telic explainability of opaque agents
- Conduct the design and training of models for explainable AI
- Design and lead the experiments of the models with virtual or physical agents
- Implement reliable, reproducible and automated training and evaluation methodologies
- Lead the efforts in integrating and exploiting the work done in other HPAI projects where it may be applicable
- Document and disseminate the work done
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Education
- Degree in STEM
-
Essential Knowledge and Professional Experience
- Experience in a research-oriented position (one year minimum)
- Experience in writing scientific papers (one pair-reviewed paper minimum)
- Experience in explainable AI, esp. focused on agents (one year minimum)
- Experience in reinforcement learning (six months minimum)
- Experience in intelligent agent architectures (six months minimum)
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Additional Knowledge and Professional Experience
- Fluent English and Spanish are a must. Catalan is desirable.
- Mathematical and formal logics background is desirable
-
Competences
- Ability to work in multidisciplinary environments
- 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
- Duration: 4 years
- Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement
- Salary: 42.000,00€
- 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 2024
- 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.
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.
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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