Applied Research Scientist in Robot Learning & Manipulation
3 days ago
Cerdanyola del Vallès
ph3Position Overview /h3 pPermanent position – Robotics AI – GRAIL European flagship project – Barcelona area – Hybrid work. /p pAre 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 bEurecat Technology Centre /b 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. /p h3Why this role matters? /h3 pRobotics 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. /p h3What will you work on? /h3 ul liImitation learning, reinforcement learning, or related approaches for robotic manipulation and mobile manipulation skill acquisition. /li liFoundation models for robotics, including multimodal and vision‑language‑action approaches, that can generalise across tasks, objects, environments, or robotic platforms. /li liIntegration and validation of AI methods on real robotic systems. /li liHuman‑robot collaboration and manipulation in industrial or semi‑structured environments. /li liScientific publications, project deliverables, demonstrations, and collaboration with European partners. /li /ul pYou will work on both simulations and real‑world robotic systems, focusing on developing, implementing, testing, and refining innovative ideas to meet practical constraints. /p h3Requirements: What are we looking for? /h3 pWe 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. /p h3Essential /h3 ul liPhD in Robotics, Artificial Intelligence, Machine Learning, Computer Vision, Control, or a related field; or equivalent research experience. /li liStrong background in machine learning or deep learning applied to robotics. /li liExperience with robot learning, manipulation, embodied AI, learning for control, or AI‑based robotic perception/action. /li liStrong programming skills in Python. /li liAbility to work with real robotic systems, not only offline datasets or simulation. /li liScientific and technical maturity: ability to define problems, test hypotheses, analyse results, and communicate findings. /li liGood written and spoken English. /li /ul h3Highly valuable /h3 ul liExperience with imitation learning, behaviour cloning, reinforcement learning, offline RL, diffusion policies, transformers, VLA models, or foundation models for robotics. /li liExperience with ROS/ROS 2. /li liExperience with PyTorch, TensorFlow, or similar frameworks. /li liExperience with robotic arms, mobile manipulators, force/contact‑rich manipulation, bimanual manipulation, or human‑robot collaboration. /li liPublications, open‑source contributions, project demos, or research prototypes in robot learning or embodied AI. /li liExperience in European or collaborative RD projects. /li /ul h3This role is probably a good fit if… /h3 ul liYou have worked on AI methods that make robots perceive, decide, manipulate, adapt, or learn. /li liYou enjoy both research and implementation. /li liYou are comfortable moving between papers, code, experiments, robots, and project discussions. /li liYou want to work in applied research: scientifically ambitious, but connected to real systems and industrial impact. /li liYou are attracted by the opportunity to contribute to a European flagship effort in robotics foundation models. /li /ul h3This role is probably not the best fit if… /h3 ul liGeneric object detection without a connection to robot action or manipulation. /li liLLM chatbot development without robotics. /li liPure navigation, PLC programming, or classical control with no AI/robot‑learning component. /li liSimulation‑only research with no interest in deploying on real robots. /li liSoftware front‑end or general AI engineering unrelated to physical robotic systems. /li /ul h3Benefits /h3 ul liPermanent contract. /li liHybrid work. /li liFlexible schedule. /li liShorter workday on Fridays and summer schedule. /li liFlexible compensation package: health insurance, transport, lunch vouchers, training, kindergarten, and other benefits. /li liAccess to Eurecat Academy courses. /li liLanguage training in English, Catalan, and Spanish. /li liParticipation in a major European robotics and AI project with leading academic and industrial partners. /li liThe opportunity to build long‑term research lines beyond a single project. /li /ul /p #J-18808-Ljbffr
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