Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%. In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career. Industry and manufacturing have the potential to enhance current monitoring and control systems that employ sensing systems such as RFID by allowing instant access to the information these systems collect. Emerging conversational user interfaces (CUI) such as Apple Siri® are a very powerful input/output mechanism for information/knowledge retrieval. Powered by the latest technological developments in deep learning, industrial wearables and novel CUIs need to support users to obtain information and knowledge from the diverse range of ubiquitous sensor-enabled items that are found more commonly in industrial organisations. The Embedded Intelligent Integrated Systems Group at the Wolfson School of Mechanical, Manufacturing and Electrical Engineering works actively with industrial collaborators to develop and industrially deploy adaptive intelligent systems and their related software services (e.g. analytics, visualisation, multimodal interaction) with particular emphasis on developing methods and systems in harsh industrial environments characterised by imperfect knowledge and uncertainty. The Embedded Intelligent Integrated Systems Group is looking for a PhD candidate with interest and skills in machine learning and conversational user interfaces. The research topic will be specifically defined based on the background and interests of the applicant after acceptance. Applicants should have a strong background in mathematics and algorithms, excellent writing skills, and experience or genuine interest in intelligent multimodal advisory systems. Prior research experience in machine learning and related fields will be a plus. Applicants are expected to have also a solid background in programming (e.g. C++, python) and computational techniques and demonstrate an interest to work in interdisciplinary research environments.