Are you excited about building the next generation of robots that can understand situations, reason about goals, deliberate under uncertainty, and act in the physical world?

The Cognitive Robotics Group within the Robotics and Automation Unit at Eurecat Technology Centre is looking for an Applied Research Scientist in Cognitive Robotics and Robot Reasoning.

You will work on GRAIL (Grant Agreement No. ) - a flagship European project developing foundation models for robotics - and continue contributing to Eurecat's cognitive robotics roadmap beyond the project. This is a permanent research position.

We are looking for someone with PhD-level research maturity - either through a completed PhD or equivalent research experience - and hands‑on experience applying AI/ML, reasoning, planning, or foundation-model methods to robotic systems.

Why this role matters

Robotics is entering a new phase: generative AI and foundation models are changing how robots perceive, interpret, decide, and acquire new capabilities. But robotics is not only language. Robots need grounded reasoning, spatial and semantic world understanding, memory, uncertainty handling, safety, and a reliable connection between deliberation and physical action.

In this role, you will help bridge that gap: turning advanced AI methods into cognitive robotic capabilities for task reasoning, situational grounding, world modelling, and decision‑making in real industrial and semi‑structured environments.

This is a unique opportunity to work with some of the strongest robotics and AI groups in Europe on a project that aims to shape the future of physical AI and industrial automation. If you want your research to move beyond papers and benchmarks into real robotic systems that reason,



explain, adapt, and act, this is the kind of opportunity you should not miss.

What You Will Work On

You will contribute to applied research and development in areas such as:

- Robot reasoning, deliberation, task planning, and decision‑making for embodied agents operating under uncertainty.
- Foundation models for robotics, including multimodal models that connect language, vision, knowledge, memory, scene understanding, and action‑relevant representations.
- Design and implementation of new robotics‑oriented AI architectures and agentic systems, combining foundation models with planners, memory, tool use, world models, verifiers, simulators, and robot‑action interfaces.
- Grounding of reasoning in the physical world: object and scene understanding, affordances, spatial/semantic context, task constraints, human instructions, and feedback from real robot execution.
- Predictive world models, simulation‑supported reasoning, data‑driven adaptation, and methods that help robots generalise across tasks, environments, objects, and platforms.
- Scientific publications, project deliverables, demonstrations, and collaboration with European partners from robotics, AI, industry, and human‑centred technology.

You will not be working only on isolated academic benchmarks or language‑only prototypes.



The role involves developing ideas, implementing them, testing them with robotic systems and realistic tasks, and adapting them to practical constraints.

Requirements

What We Are 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 cognitive robotic systems.

Essential

- PhD in Robotics, Artificial Intelligence, Machine Learning, Computer Vision, Cognitive Systems, Automated Planning, or a related field; or equivalent research experience.
- Strong background in machine learning, deep learning, symbolic/neural reasoning, planning, or foundation models applied to robotics or embodied AI.
- Hands‑on experience designing, training, fine‑tuning, or adapting AI model architectures for robotics or embodied AI, including implementation choices around data, losses, evaluation, and deployment - not only API use or prompt engineering.
- Experience connecting perception, language, knowledge representations, planning, decision‑making, and action in embodied or robotic systems.
- Strong programming skills in Python.
- Ability to work with real robotic systems, experimental platforms, or realistic robotic demonstrators - not only offline datasets or simulation.
- Scientific and technical maturity: ability to define problems, test hypotheses, analyse results, integrate components, and communicate findings clearly.
- Good written and spoken English.

Highly valuable

- Experience with LLMs, VLMs, multimodal foundation models, transformers, neuro‑symbolic methods, task and motion planning, hierarchical planning, memory architectures, or uncertai

📌 Applied Research Scientist in Cognitive Robotics (Sardañola del Vallés)
🏢 Eurecat - Centro Tecnológico
📍 Sardañola del Vallés