Postdoctoral researcher in multimodal data integration and correlation analysis
Pubblicato il 04-10-2026 - Aretè & Cocchi Technology in Napoli
Postdoctoral researcher in multimodal data integration and correlation analysis
Postdoctoral researcher in multimodal data integration and correlation analysis
Italy
Commitment & contract: 19 months Post-Doc position
Location: Center for Advanced Biomaterials for Health Care (CABHC), Naples
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 multicultural and multi-disciplinary group, where junior and senior scientists collaborate, each with their expertise, to carry out a scientific activity with a shared research goal.
The Bio-logic Research unit is coordinated by Prof. Paolo Netti. The research focuses on the quantitative integration and correlation of multimodal datasets generated from advanced in vitro systems, with particular emphasis on identifying relationships between electrophysiological, structural, imaging, and biochemical readouts. The activity will contribute to the development of data-driven approaches for the identification of quantitative patterns and functional signatures associated with physiolog