Prestigious EPSRC Funded Postdoctoral Research Associate – Fixed Term For Up To 48 Months

Programme: COG-MHEAR - world’s first cognitively-inspired multi-modal hearing aid. 

Funding: £4 million (fEC), Engineering and Physical Sciences Research Council (EPSRC), UK Government. 

Academic Partners: Edinburgh Napier (Lead), Wolverhampton (Co-Lead), Manchester, Edinburgh, Heriot-Watt, Glasgow, Nottingham, and University College London. 

Industrial Partners: Nokia Bell Labs, Sonova, and Alpha Data. 

Conscious Multisensory Integration (CMI) Lab is leading several National and International prestigious projects in collaboration with world-leading academics, agencies, and industries, including NASA, Intel, Qualcomm, and ARM.

As part of our ~£4 million COG-MHEAR programme grant funded by the EPSRC, we are co-pioneering the world’s first multimodal (MM) audio-visual hearing aid (HA) by radically exploiting and integrating the transformative potential of privacy-assuring and explainable AI, 5G, IoT and cybersecurity, coupled with flexible (skin-based) electronics. Our vision 2050 is to develop a full system-on-chip MM HA that will be internet-independent.

We are looking to appoint a full-time exceptional Researcher to undertake world-leading research in one or more individual COG-MHEAR projects, working on internet-independent on-chip big data processing, privacy-preserving context-sensitive machine learning, and MM audio-visual speech enhancement.

This is an exceptional opportunity to drive ambitious pioneering research and become a part of the EPSRC Programme.

Qualifications:

  • PhD/ equivalent experience in machine learning, computational neuroscience, computer science, quantum computing, applied mathematics, robotics, cognitive science, engineering or related fields.
  • Strong understanding of energy-efficient/ low power deep learning approaches and other latest techniques in the areas of probabilistic learning, spiking neural nets, graph neural nets, deep language models, transfer and representation learning.
  • Hands-on experience in implementing deep learning approaches using Matlab, Tensorflow, Pytorch.
  • World-class research experience and strong relevant publications record in top journals and conferences.
  • Track-record of contributing to funding proposals and making effective independent contributions to collaborative research teams.
  • Demonstrated ability to solve real-world problems independently and make original contributions to research.
  • Main Duties and Responsibilities:

  • Undertake world-leading research in one or more individual COG-MHEAR project, working on privacy-preserving energy-efficient machine learning and multi-modal speech enhancement.
  • Undertake management, supervision and administrative responsibilities associated with research duties.
  • Preparation of peer-reviewed publications for quality journals, conferences and dissemination of research results at international and national conferences.
  • Plan and manage your own research activity in collaboration with other COG-MHEAR project teams.
  • Participate in external research networks or appropriate events in order to build new relationships, exchange ideas and disseminate findings, including through the development of relationships with researchers, PhD students and COG-MHEAR User-Group members.
  • Regular liaison with other COG-MHEAR 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.
  • Salary: £31,800 to £34,800.

    Closing date: 12 April 2021 (only short-listed candidates will be contacted).

    Informal inquiries can be made to Dr Ahsan Adeel (ahsan.adeel@deepci.org).

    Prestigious EPSRC match funded PhD Studentships

    Three positions are available. 

    Projects: 

    1. COG-MHEAR - world’s first cognitively-inspired multi-modal hearing aid - see details above.  

    2. Novel brain-inspired energy-efficient high-performance computing architectures.

    3. Context-sensitive probabilistic deep learning.

    Qualifications:

    Candidates must be willing to travel to other project sites, including short visits to the University of Oxford, Edinburgh, Manchester, and Glasgow.

    Studentship covers UK/EU tuition fee and provides a tax-free stipend of £15,500 pa.

    Closing date: Until the posts are filled (only short-listed candidates will be contacted).

    Informal inquiries can be made to Dr Ahsan Adeel (ahsan.adeel@deepci.org).

    PhD Positions 

    [This job has expired]

    As part of our 4 years of collaborative doctoral partnership (CDP) and AI research programme, in collaboration with the Massachusetts Institute of Technology (MIT), University of Oxford, and Nottingham Trent University (NTU), we seek applicants for 5 PhD fellowships. More details will follow shortly.

    Knowledge and Experience:

    Entrants must have a first/undergraduate Honours degree, with a First-Class grade. Applicants with an Upper Second Class must also have a postgraduate master’s degree at Merit. A GPA higher than 3.8/4.0 (for international students)

    Candidates must be willing to travel to other project sites for collaboration (including short visits to the University of Oxford and NTU).

    please send your CV to ahsan.adeel@deepci.org