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    News: upcoming academic positions

    The EEE department are expecting to advertise 3 academic positions within the next two months. We hope to draw a strong pool of candidates for each of these important roles within the department.

    A further announcement will be made once these posts are live and available for applications on the Imperial College Jobs website:

    2 x Lectureships in Robotics & Machine Learning

    Applicants will be sought within the areas of Computer Vision and Machine Learning. The research areas of interest include (but not limited to) computer vision and machine learning for real-time domains such as healthcare monitoring, multimodal human-machine interaction, robotics, autonomous vehicles, and smart cities. Applicants that combine computer vision or machine learning with engineering applications in the wider area of intelligent systems will also be welcomed.

    The post will combine research activity with teaching including planning programmes of outstanding international quality, publishing in high quality journals and successfully attracting funding. Teaching will involve courses at undergraduate and postgraduate levels including undergraduate, Master’s and higher research degree students through lectures, seminars, course work, tutorials and personal supervision. In addition, the supervision of laboratory and design groups.

    1 x Lecturer in the general area of statistical signal processing and wireless communications

    In the general area of statistical signal processing and wireless communications. Topics of interest include, but are not limited to, intelligent signal processing, statistical signal processing, intelligent communications, semantic communications, coding and information theory, wireless communication theory and systems, cross-layer design and cooperative communications.

    In addition to core expertise in signal processing and communications, we would welcome candidates with strong interest in cross-disciplinary research in applied maths and machine learning for signal processing and communications.


PhD students