Post Title: Research Fellow in AI/ML for Optimising Wireless Networks and Devices
SBU/Department: School of Physics, Engineering and Computer Science
FTE: 1 FTE (working 37 hours per week)
Duration of Contract: Fixed term (Until May 2026)
Salary: UH7 £35,333 pa with potential to progress to £42,155 pa on achieving designated skills and experience
Location: College Lane Campus, Hatfield

Main duties and responsibilities
As the successful candidate you will propose and develop AI algorithms for future wireless networks. You will design proactive resource allocation using data analytics algorithms, develop program codes for conducting simulations and develop AI-on-hardware testbed for IoT and wireless communications. In addition, you will carry out other specific duties as may be reasonably requested by the academic leader and that are commensurate with the nature and grade of the post. Collaboration with co-workers within the Communications and Intelligent Systems Research Group, other Higher Education Institutions, and other relevant bodies is essential.

You will seek external funding as appropriate and disseminate the outcomes of the conducted research in publications, high quality academic journals, conferences and through other appropriate media. You will also undertake undergraduate and post-graduate teaching as specified in the annex. Furthermore, you will create opportunities to maximise research activities, capturing relevant evidence to support impact and engaging with external partners and stakeholders.

Skill and experience required
Significant experience of developing and analysing signal processing/machine learning algorithms for wireless communications OR significant experience of using edge computing architectures (AI-on-hardware) for wireless communications. Strong and proven track record of publishing high-quality research results in top international journals and conference proceedings in the relevant areas.

The post holder will require significant experience with wireless communications and/or IoT systems. Excellent programming skills in Python with AI/ML libraries (Scikit-Learn, TensorFlow etc), and/or VerilogHDL/VHDL. Excellent written and oral communication, and IT skills. Excellent analytical skills and problem-solving skills. Self-motivated with ability to meet deadlines. Ability to work independently and as part of a team, engaging with different academic and industrial partners. Excellent interpersonal, and organisational skills. Willingness to undertake appropriate further training and to adopt new procedures as and when required.

Desirable skills are experience in deep learning and/or reinforcement learning for communications/IoT; experience in AI-on-hardware (edge computing) for communications/IoT; Ability to assist in teaching of undergraduate or postgraduate students; experience in testing wireless devices and links in lab environment.

Qualifications required
You will require an undergraduate honours degree at a minimum 2:1 (or equivalent) in a relevant discipline and a PhD (or equivalent qualification), or close to completion of PhD (no more than 3 months prior to viva) in a relevant subject area, or equivalent experience.

Please view the job description and person specification for a full list of the duties and essential criteria.

An appointment to this role may require an Academic Technology Approval Scheme (ATAS) certificate.
Contact Details/Informal Enquiries: Dr Iosif Mporas, i.mporas@herts.ac.uk

Closing Date: 11 April 2023
Interview Date: Week commencing 17 April 2023
Reference Number: 050055
Date advert placed: 24 February 2023

Our vision is to transform lives and UH is committed to Equality, Diversity and Inclusion and building a diverse community. We welcome applications from suitably qualified and eligible candidates regardless of their protected characteristics, and recognise there are different ways applicants may achieve the criteria in this document. We offer a range of employee benefits including generous annual leave, flexible location opportunities within the UK, discounted Sports Village memberships, personal and professional development and family-friendly policies. #GoHerts