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Research Fellow (COG-MHEAR)

Edinburgh Napier University

Location: Edinburgh
Salary: £34,308 to £40,931 per annum / pro rata (Grade 5)
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 9th December 2022
Closes: 3rd January 2023
Job Ref: 0000515757
 

Edinburgh Napier University is seeking to appoint a full-time (or part-time) Research Fellow for the prestigious EPSRC funded Programme Grant: COG-MHEAR, led by Programme Director (PD): Professor Amir Hussain, based in the School of Computing. The work may involve conducting related research as part of the EPSRC funded project on Natural Language Generation for Low-Resource Domains (NATGEN), jointly led by Dr. Dimitra Gkatzia and Prof. Amir Hussain.

COG-MHEAR is a world-leading cross-disciplinary research programme funded under the EPSRC Transformative Healthcare Technologies 2050 Call. It aims to develop the world’s first multi-modal hearing-aid demonstrators by radically exploiting and integrating the transformative potential of privacy-assuring and explainable AI, 5G, IoT, wireless sensing and cybersecurity, coupled with flexible (skin-based) electronics. More details on: http://cogmhear.org.uk

NATGEN is pioneering the development of privacy-preserving and emotion-sensitive conversational agents for natural language dialogue in low-resource domains. This is aimed at helping improve the mental health of young people.

Further information about the School of Computing can be found here. Additional facts and figures on the University can be found here.  

The role

The role involves taking a leading research role in one or more individual, collaborative project in COG-MHEAR and supporting priority NATGEN project areas, under the direction of Prof. Hussain. Flexible part-time appointments may also be considered.

Responsibilities

Reporting to Prof. Hussain, the post-holder will:

  • Undertake world-leading research in one or more priority COG-MHEAR and NATGEN project areas, involving development of trustworthy machine learning approaches for audio-visual speech enhancement and conversational agents. Current priority areas for the Research Fellow include the followings:
  • Real-time audio-visual (AV) speech enhancement in multi-modal real-life and AR/VR environments, with a focus on privacy-preserving/federated and explainable machine/transfer learning models, AV beamforming and large-scale optimisation for low-energy, mobile/edge and on-chip systems. (COG-MHEAR priority area)
  • Emotion-sensitive, multi-modal natural language processing/generation and evaluation of conversational agents in low-resource domains. (NATGEN priority area with links to related COG-MHEAR projects on multi-modal cognitive load/listening effort-aware AV speech enhancement in real-life and AR/VR environments).
  • Real-time 5G-IoT and wireless sensing enabled AV hearing-aid prototype development, including exploring novel approaches to MEMS (micro-electromechanical systems) antenna integration and brain-inspired flexible/quantum-electronics based wearable implementations. (COG-MHEAR priority area - this work may involve stays at the Universities of Glasgow and Manchester).

Undertake management, supervision and administrative responsibilities associated with research duties

  • Preparation of peer-reviewed publications for high-impact journals, conferences and dissemination of research results at international and national conferences.
  • Plan and manage own research activity in collaboration with other COG-MHEAR project teams
  • Regular liaison with other COG-MHEAR and NATGEN project researchers, our collaborating companies, clinicians and end-users in the User-Group to ensure overall programme goals are met
  • Develop and contribute to proposals to secure future research funding
  • Undertake other activities as appropriate to COG-MHEAR and NATGEN, under the direction of the PD

Who we are looking for

A highly motivated and enthusiastic individual who brings:

  • World-class research experience in machine learning, audio-visual speech processing, hearing-aid signal processing, natural language processing/generation, high performance computing or related areas
  • A strong relevant publication record in top journals and conferences
  • A track-record of contributing to funding proposals and making effective independent contributions to collaborative research teams
  • a demonstrated ability to solve real-world problems independently and make original contributions to research
  • Excellent programming and quantitative research and teamworking skills
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