Position Overview
Permanent position – Robotics & AI – GRAIL European flagship project – Barcelona area – Hybrid work.
Are you excited about building the next generation of robots that can learn, adapt, and act in the physical world? The Robotics and Automation Unit at Eurecat Technology Centre is looking for an Applied Research Scientist in Robot Learning and Manipulation. This permanent research position focuses on GRAIL (Grant Agreement No. ), a lighthouse European project to develop foundation models for robotics, emphasizing real‑world validation on robotic hardware and industrial use cases.
Why this role matters?
Robotics is entering a new phase: generative AI changes how robots perceive, decide, and acquire new skills. Robotics is not just about language. Robots must deal with contact, uncertainty, limited data, hardware constraints, safety, and the messy complexity of the physical world. In this role, you will help bridge that gap: turning advanced AI methods into robust robotic capabilities for manipulation and safe human‑robot collaboration in real industrial environments.
What will you work on?
- Imitation learning, reinforcement learning, or related approaches for robotic manipulation and mobile manipulation skill acquisition.
- Foundation models for robotics, including multimodal and vision‑language‑action approaches, that can generalise across tasks, objects, environments, or robotic platforms.
- Integration and validation of AI methods on real robotic systems.
- Human‑robot collaboration and manipulation in industrial or semi‑structured environments.
- Scientific publications, project deliverables, demonstrations, and collaboration with European partners.
You will work on both simulations and real‑world robotic systems, focusing on developing, implementing, testing, and refining innovative ideas to meet practical constraints.
Requirements: What are we looking for?
We do not expect you to match every keyword. We are looking for depth, curiosity, and the ability to turn research ideas into working robotic systems.
Essential
- PhD in Robotics, Artificial Intelligence, Machine Learning, Computer Vision, Control, or a related field; or equivalent research experience.
- Strong background in machine learning or deep learning applied to robotics.
- Experience with robot learning, manipulation, embodied AI, learning for control, or AI‑based robotic perception/action.
- Strong programming skills in Python.
- Ability to work with real robotic systems, not only offline datasets or simulation.
- Scientific and technical maturity: ability to define problems, test hypotheses, analyse results, and communicate findings.
- Good written and spoken English.
Highly valuable
- Experience with imitation learning, behaviour cloning, reinforcement learning, offline RL, diffusion policies, transformers, VLA models, or foundation models for robotics.
- Experience with ROS/ROS 2.
- Experience with PyTorch, TensorFlow, or similar frameworks.
- Experience with robotic arms, mobile manipulators, force/contact‑rich manipulation, bimanual manipulation, or human‑robot collaboration.
- Publications, open‑source contributions, project demos, or research prototypes in robot learning or embodied AI.
- Experience in European or collaborative R&D; projects.
This role is probably a good fit if…
- You have worked on AI methods that make robots perceive, decide, manipulate, adapt, or learn.
- You enjoy both research and implementation.
- You are comfortable moving between papers, code, experiments, robots, and project discussions.
- You want to work in applied research: scientifically ambitious, but connected to real systems and industrial impact.
- You are attracted by the opportunity to contribute to a European flagship effort in robotics foundation models.
This role is probably not the best fit if…
- Generic object detection without a connection to robot action or manipulation.
- LLM chatbot development without robotics.
- Pure navigation, PLC programming, or classical control with no AI/robot‑learning component.
- Simulation‑only research with no interest in deploying on real robots.
- Software front‑end or general AI engineering unrelated to physical robotic systems.
Benefits
- Permanent contract.
- Hybrid work.
- Flexible schedule.
- Shorter workday on Fridays and summer schedule.
- Versátil compensation package: health insurance, transport, lunch vouchers, training, kindergarten, and other benefits.
- Access to Eurecat Academy courses.
- Language training in English, Catalan, and Spanish.
- Participation in a major European robotics and AI project with leading academic and industrial partners.
- The opportunity to build long‑term research lines beyond a single project.
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