Applications are invited for a Research Associate (PostDoc) or Research Assistant (RA) who is about to receive their PhD, to join the Affective Intelligence and Robotics Lab in the Department of Computer Science and Technology, at the University of Cambridge, UK (The Cambridge AFAR Lab: https://cambridge-afar.github.io/). The Research Associate / Research Assistant (RA) will ideally start the post on 1st of September 2025 (or earliest thereof), and will work on the MICRO Project (https://chanse.org/micro/ ).
The RA will be supervised by Prof Hatice Gunes, Prof Jenny Gibson and Prof Tamsin Ford in Cambridge and will work closely with the other members of the multi-national and multi-disciplinary team of researchers from Uppsala University (Sweden), ETH Zürich (Switzerland) and Bielefeld University, Germany on measuring children’s wellbeing and mental health with social robots. The specific focus of the RA will be on: 1) assisting in the design and undertaking of child-robot interaction studies, and 2) applying signal processing and machine learning methodologies for child-robot multimodal and interactive behaviour analysis and understanding to facilitate AI based child mental wellbeing and mental health prediction.
Essential Requirements
The ideal candidate will possess experience with designing and running user studies with social robots, and in particular children, as well as hands-on experience in implementing state-of-the-art machine learning models and architectures (e.g., deep learning, graph neural networks or reinforcement learning), and deploying them for real-time analysis of human behaviours. The Cambridge AFAR Lab focuses on developing novel machine learning and autonomous human-robot interaction frameworks and deploying them in real time and/or real-world settings. Therefore, we require someone with excellent implementation skills, and experience with autonomous robotic system deployments. A high degree of self-motivation, research-oriented thinking, and a drive for creating autonomous robotic systems to run in real-time are all essential traits for this position.
Desirable Skills
It is desirable that the candidate has experience in implementing or using state-of-the-art machine learning methodologies for real-time analysis of human behaviour, and/or experience in designing and running child-robot interaction studies, and/or has experience using Large Language Models (LLMs) for research and/or user studies, and/or has an interest (or experience) in undertaking HRI user studies related to health and wellbeing.
Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded. Candidates who have an MSc/MPhil but are not working towards the completion of a PhD degree are discouraged from applying.
The Department of Computer Science and Technology is an academic department that encompasses computer science along with many aspects of engineering, technology, and mathematics. We have a world-wide reputation for academic research with consistent top research ratings. The Department has an open and collaborative culture, supporting revolutionary fundamental computer science research, strong cross-cutting collaborations internally and externally, and ideas which transform computing outside the University. Please follow the link at: https://www.cst.cam.ac.uk to find out more about our Department.
If applicants require further information, they should contact Professor Hatice Gunes (http://www.cl.cam.ac.uk/~hg410/).
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The University has a responsibility to ensure that all employees are eligible to live and work in the UK. Please note that we provide the support of applying for the relevant visa (if required) and we reimburse the cost of the first visa.
Required documents include a cover letter, a curriculum vitae, a brief research statement, and contact information for two references. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please quote reference NR45269 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
