Job Reference : 660_24_CS_HPAI_RE2 Position : Research Engineer - Agent-based models for transfer learning - AI4S (RE2) Closing Date : Monday, 30 September, 2024 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 MareNostrum, one of the most powerful supercomputers 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.
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.
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 peer-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 : 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... #J-18808-Ljbffr