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Details of Studentship: We are recruiting three fully-funded PhD students to work alongside our new UKRI-funded £6.5M research programme in Somabotics: Creatively Embodying Artificial Intelligence led by Professor Steve Benford. Somabotics will explore new kinds of creative interaction between humans and AI, especially robots. You will join a multidisciplinary team of twelve researchers and work with renowned artists to create, tour, and study high-profile artworks that will demonstrate how humans can interact with robots in more meaningful ways. Through this, you will contribute novel foundational concepts, methods and tools for artificial intelligence. You can find out more about Somabotics and explore examples of our recent work here in Professor Benford’s website. You will benefit from:
There will be extensive opportunities for travel, including for additional training activities (e.g., Summer Schools and Doctorial Colloquia), participating in conferences, and visits to international and industry partners. We are seeking students from various disciplinary backgrounds to work in our multi-disciplinary team, including soft robotics, creative artificial intelligence, human-robot interaction, artist-led research, and somaesthetic design. Please see below for some examples of possible PhD topics We are interested in your interpretation of these and your response to our wider vision of Somabotics. Entry Requirements:
Application Process: Applicants to initially contact Steve Benford Applications must be submitted via the University’s PhD application website. More information on how to apply can be found here.
Enquiries to be directed to: Professor Steve Benford, Steve.benford@nottingham.ac.uk. Official applications must be via My Nottingham Example research topics Soma Skins – we envisage soma skins to be a new kind of technology that mediates physical interaction between humans and robots. They might, for example, be soft materials with embedded sensors and actuators that can dress both human and robot bodies to capture data about mutual touch while delivering sensation to guide interaction in return. The PhD might focus on the design and prototyping of soma skins, possible artistic applications, the manufacture of crafting of sensors and actuators into materials, or the data that soma skins would generate and utilise. Improvising with AI – we wish to explore how humans and AI can improvise together during live performance, for example when playing music together as part of an ensemble. The PhD might focus on developing new AI models, driving and evaluating these through live performance. It might also consider how humans would interact with such models, for example by embedding interfaces into augmented musical instruments or robot musicians. AI and feelings – we wish to explore the role of ‘feelings’ in our interactions with AI. Feelings occupy an ambiguous place between our conscious thoughts and our pre-conscious emotions and sensations – they are the point at which our emptions become apparent to ourselves, so we can name and describe them. The PhD will l look beyond current research in emotion detection to explore how AI and robots can engage messy and ambiguous world of human feelings through applications spanning art and wellbeing. How might such as AI help us better understand our own feelings? This PhD would be in partnership with and supported by our partner Blueskeye, an AI company who developing emotion recognition for applications including Healthcare, Well-being, and Social Robotics. Documentation, datasets and archives – AI is dependent on datasets, which may be made public in archives as a resource for the research community. In turn, art is dependent on rich documentation which may be generated during the artistic process so that it could be used by scholars and curators to study, exhibit and reactivate archived artworks. This PhD will explore the relationship between artworks’ datasets and documentation – what are their similarities and differences? How can best practice in art documentation enhance AI datasets? And how in turn, can AI support the documentation of artworks?
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