AI & Emerging technologies

Research Associate in Human-Robot Interaction

King's College London

London · Greater London · United Kingdom

Overview

In this role you advance socially intelligent assistive robots for future healthcare within the CO-STAR programme. You will join SAIR in the Department of Engineering and collaborate with NHS professionals to translate research into real-world clinical settings. You will shape multidisciplinary studies in human–robot interaction, machine learning, and healthcare robotics, delivering novel systems and evidence of impact. The work combines cutting-edge AI with human-centred design in a living lab environment, contributing to teams across academia and clinical practice. This position offers a meaningful opportunity to influence technology that supports patients and clinicians while advancing an

Responsibilities
  • shape and conduct high-quality multidisciplinary research within the CO-STAR project
  • develop novel methods in human–robot interaction, machine learning, and socially intelligent robotics
  • design, implement, and evaluate robotic and AI systems within healthcare robotics scope
  • disseminate findings through publications and international conferences
  • contribute to activities that maximise academic, clinical, and societal impact
  • collaborate with the project team and GSTT to translate research into real-world healthcare settings
Key requirements
  • PhD awarded (or near completion) in a relevant field
  • strong research background in socially aware or human-centered AI, ML, robotics, and/or HRI
  • strong publication record in peer-reviewed venues (ICRA, IROS, RA-L, CoRL, etc.)
  • excellent Python programming skills and experience with deep learning frameworks
  • experience with ROS and physical robotic platforms or simulations
  • excellent written and verbal communication skills for academic and non-academic audiences
  • collaborative in multidisciplinary environments
  • clear scientific communication
  • ability to work with diverse stakeholders (clinicians, patients, engineers)
  • Python programming with deep learning frameworks
  • Robot Operating System (ROS)
  • multimodal machine learning

Reference: WJ-747_31165992

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