Istituto Italiano di Tecnologia

Research fellow for Reinforcement Learning for Humanoid Robot Co-Design

Italy

Location: 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 join the multi-disciplinary team of developers and designers at the Artificial Mechanical and Intelligence Research Unit, where researchers and engineers collaborate altogether, each with their own expertise, to carry out common research.

Within the team, your main responsibilities will be:

  • Develop hardware-accelerated simulation environments for the co-design of humanoid robots.
  • Design and implement algorithms that leverage  learning techniques to identify optimal humanoid robot characteristics and behaviors.
  • Conduct experiments on real robotic platforms to evaluate hardware limitations and validate simulation results.
  • Explore the synergy between morphology and control by optimizing both the robot's physical design and its control strategies.

This open position/research is funded by INAIL within the project "ErgoCub-2.0 - Gestione integrata, predittiva e responsabile dei profili di rischio dei nuovi contesti lavorativi ibridi: collaborazione uomo-robot e intelligenza artificiale" (CUP J53C2400054005)

ESSENTIAL REQUIREMENTS

  • A Master or PhD degree in Robotics Engineering, Mechatronics, Computer Science, or a related field.
  • Experience with programming languages such as  C++ and Python.
  • A research-oriented mindset with the ability to translate innovative concepts into functional and manufacturable products.
  • Creative and proactive attitude, with strong problem-solving skills.
  • Excellent communication skills and the ability to work collaboratively in a multidisciplinary team.
  • Proficient in English, both written and oral.

ADDITIONAL SKILLS

  • Experience in robot control.
  • Experience in Reinforcement Learning.
  • Hands-on experience with real robotic platforms.
  • Experience with industrial robotics software environments.
  • Knowledge of mathematical optimization techniques applied to mechanical systems.
  • High motivation to learn and take initiative.
  • Strong organizational skills, with the ability to manage time and priorities effectively.
  • Ability to thrive in a challenging, fast-paced, and international research environment.
  • Capacity to work independently as well as collaboratively in highly interdisciplinary teams.

COMPENSATION & BENEFITS

  • Competitive salary for international standards 
  • Wide range of staff discounts.
  • Candidates from abroad or Italian citizens who have carried scientific research activity permanently abroad and meet specific requirements, may be entitled to a deduction from taxable income of up to 90% from 6 to 13 years.

 

Please submit your application using the online form and include a detailed CV.

Application deadline: May  30th, 2025

 

To discover more about life at IIT, visit the dedicated section here: https://www.iit.it/en/work-at-iit

Loading...

Apply now

Fill in the form below and send your application.

By marking the checkbox, you accept our privacy policy
You must accept the treatment of personal data