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<div class="">A PhD studentship is available at the University of Manchester, as part of a collaboration with the industrial partner BAE Systems.</div>
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<p class="MsoNormal"><b class="">Project Title: Human-Robot Collaboration for Flexible Manufacturing (iCase PhD Studentship)</b><o:p class=""></o:p></p>
<p class="MsoNormal">Academic Supervisor: Angelo Cangelosi, <o:p class=""></o:p>University of Manchester (Cognitive Robotics Lab, Department of Computer Science)</p>
<p class="MsoNormal">Industrial Supervisor: Alex Griffiths, Austin Cook, BAE Systems<o:p class=""></o:p></p>
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<p class="MsoNormal"><b class="">PhD Project Overview:<o:p class=""></o:p></b></p>
<p class="MsoNormal">As manufacturers of high complexity, low volume products with considerable variation in build standards, one obstacle to our adoption of widespread robotics in the manufacturing process is the amount of programming required - it is currently
difficult to see sufficient return on investment. The ability for the robot to understand what is required during collaboration with people to produce a solution autonomously and via imitation learning, would drastically reduce programming times, resulting
in agile, reconfigurable manufacturing.</p>
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<p class="MsoNormal">Current robotics and AI research on human-robot interaction and collaboration between people and cobots (collaborative robots) has led to the design of machine learning models of intention recognition, e.g. for the prediction of the goal
of a cooperative task and for action learning via kinaesthetic imitation and linguistic instruction. These models have been developed for simplified joint task scenarios, in laboratory settings. The latest advances in AI (e.g. deep learning) offer a timely
opportunity to scale up intentional reading models for collaboration in realistic, industry setting scenarios. This will lead to the system understanding of its environment and the components with which it is required to interact, using a combination of visual
and action recognition AI methods and interrogation of CAD models/digital twin.</p>
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<div class=""><b class="">Application requirements and Deadline</b></div>
<div class="">Undergraduate degree (First or equivalent grade) or Master degree in computer Science / Artificial intelligence of related disciplines</div>
<div class="">Studentship includes standard UK PhD bursary and UK/EU fee payment.</div>
<div class=""><b class="">Application deadline: 27 April 2020</b></div>
<div class=""><a href="https://www.cs.manchester.ac.uk/study/postgraduate-research/research-projects/description/?projectid=25920" class="">https://www.cs.manchester.ac.uk/study/postgraduate-research/research-projects/description/?projectid=25920</a></div>
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<div class="">Informal enquiry to: Professor Angelo Cangelosi <a href="mailto:angelo.cangelosi@manchester.ac.uk" class="">angelo.cangelosi@manchester.ac.uk</a> </div>
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<div><i class="">Angelo Cangelosi</i></div>
<div><i class="">Cognitive Robotics Lab</i></div>
<div><i class="">Department of Computer Science</i></div>
<i class="">University of Manchester<br class="">
<a href="mailto:angelo.cangelosi@manchester.ac.uk" class="">angelo.cangelosi@manchester.ac.uk</a></i></div>
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<i class=""><a href="https://www.research.manchester.ac.uk/portal/angelo.cangelosi.html" class="">https://www.research.manchester.ac.uk/portal/angelo.cangelosi.html</a></i></div>
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