Spain Job Openings

Barcelona Supercomputing Center (BSC)

Research Engineer – Agent-based models for transfer learning – AI4S (RE2)

Barcelona

FULL TIME

September 16, 2024

Job Reference
660_24_CS_HPAI_RE2
Position
Research Engineer – Agent-based models for transfer learning – AI4S (RE2)
Closing Date
Monday, 30 September, 2024
Reference: 660_24_CS_HPAI_RE2
Job title: Research Engineer – Agent-based models for transfer learning – AI4S (RE2)


About BSC
The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses Mare Nostrum, 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 Euro HPC 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
High-Performance Artificial Intelligence (HPAI) is an international and diverse research group that is at the forefront of innovation. HPAI conducts fundamental and responsible research in AI, ensuring that our work is always ethical and trustworthy.

We dedicate efforts to exploring and developing zero-shot transfer learning methods in the context of intelligent agents’ behaviour. The main objective of the position is to conduct research and design, implement and evaluate physical or virtual agents with adaptable embodiment such that they can perform successfully on environments they have never seen in training or when designing them. This research is in the intersection of reinforcement learning, transfer learning, game theory and cognitive 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.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

Key Duties
  • Do research in the field of zero-shot transfer learning of intelligent agents
  • Conduct the design and training of models for agents with adaptable embodiment
  • Research, design and implement appropriate environments for testing the models produced
  • 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
Requirements
  • 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 deep learning (two years minimum)
    • Experience in transfer learning (one year minimum)
    • Experience in reinforcement learning (one year minimum)
    • Experience in agent architectures (six months minimum)
  • Additional Knowledge and Professional Experience
    • Fluent English and Spanish are a must. Catalan is desirable.
    • Background in mathematics, formal logics and game theory is desirable
  • Competences
    • Ability to work in multidisciplinary environments
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
  • 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
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.
For more information follow this link

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