Technician Position For Ai Applied To Human Data And Ergonomics

07 ago - Italia
Aretè & Cocchi Technology

Technician position for AI applied to Human Data and Ergonomics (EPIC Project) Italy
Commitment & contract: Technician level 2, 2 years (extendable)
Location: IIT CRIS – Via San Quirico 19D, Genova
Step into a world of endless possibilities, together let’s leave something for the future
At IIT, we are committed to advancing human-centered Science and Technology to address the most urgent societal challenges of our era. We foster excellence in both fundamental and applied research, spanning fields such as neuroscience and cognition, humanoid technologies and robotics, artificial intelligence, nanotechnology, and material sciences, offering a truly interdisciplinary scientific experience. Our approach integrates cutting‑edge tools and technology, empowering researchers to push the limits of knowledge and innovation. With us, your curiosity will know no bounds.
We are dedicated to providing equal employment opportunities and fostering diversity in all its forms, creating an inclusive environment. We value the unique experiences, knowledge, backgrounds, cultures,



and perspectives of our people. By embracing diversity, we believe science can achieve its fullest potential.
THE ROLE You will be working in a multi-disciplinary group, where people with different backgrounds collaborate, each with their own expertise, to support IIT research activity. The Human‑Robot Interfaces and Interaction (HRI²) research line is coordinated by Dr. Arash Ajoudani. We develop intelligent robots that enable natural and human-centered interaction at both cognitive and physical levels, following a socio‑physical interaction paradigm.
Within this context, the EPIC project (Ergonomics of Physical and Cognitive Interaction in Collaboration) aims to redefine ergonomics by integrating human cognitive states and physical behavior using advanced sensing technologies and AI‑driven analysis. The project involves the acquisition and interpretation of multimodal human data (e.G., motion, behavioral cues

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