College of Business, Tech. & Engineering Academic Grade 6 - £30,487 - £37,099 per annum, dependent on experience
Please note that this is a rolling advert and may close earlier than advertised. Applications will be reviewed at regular intervals. If you are interested, please submit your application as soon as possible for consideration.
We are looking to recruit an enthusiastic postdoctoral researcher/research associate in Artificial Intelligence and Machine Learning who will support the development and application of AI-based techniques to solve real-world problems and build the capacity for AI research in our School of Engineering and Built Environment.
Artificial Intelligence is one of the key pillars of growth in both applied research and knowledge exchange within the department, and you will be expected to develop and lead your own programme of research, with the support of experienced academics.
The purpose of this role is to support the rapid growth of AI research within the department and wider university – particularly in fields such as digital health and digitisation of manufacturing processes.
We anticipate that you will develop and apply novel AI-based approaches and machine learning algorithms to solve real-world problems and contribute to the strategic development of this research area.
You will have sound knowledge in computer science, data analysis, and software engineering, as well as experience with modern AI approaches in computer vision and / or natural language processing. Knowledge of electronic engineering, embedded systems design, and Internet-of-Things / Industry 4.0 is a plus.
The position requires strong teamwork and communication skills, reliability, attention to detail, effective time management, and the ability to independently lead your own programme of research.
You will have a PhD (or be about to complete one), or have equivalent experience in Computer Science, Artificial Intelligence, or Computer Systems Engineering, including a firm grounding in developing intelligent systems.
If you have excellent computational and quantitative skills matching the above AI approaches, you are also encouraged to apply.
The Team
The Electronic Engineering and Future Technologies subject group sits within the School of Engineering and Built Environment in the College of Business, Technology, and Engineering.
We are one of the UK's leading providers of industrially focused engineering, physics, and built environment education. We have a vibrant and comprehensive portfolio, strong student recruitment and some of the best teaching, learning and research facilities in the university - benefitting from over £24m of recent STEM investment.
You will join the team at an exciting time, with rapid growth in AI research (as evidenced by a strong return in the recent REF). The Intelligent Systems and AI research within the school is aligned with the Industry and Innovation Research Institute (I2RI) and benefits from significant recent investment in high performance computing resources (including an A100 based GPU cluster).
You will be part of a vibrant team of academics, researchers, and PhD students - with more than 100 current research students across the Industry and Innovation Research Institute.
We offer a diverse range of benefits and opportunities to pursue a rewarding and fulfilling career in a supportive environment.
You will be contractually enrolled into the Teachers' Pension Scheme (TPS) – one of the largest and most generous defined benefit pension schemes in the country.
Find out more about the TPS.
If you are, or have been, a recent member of the Universities Superannuation Scheme (USS) directly prior to joining us, you can choose to opt out of the TPS and remain in the USS. Please contact the Pensions team to discuss options available.
The University may be able to sponsor the employment of international applicants in this role; this will depend on a number of factors specific to the individual applicant.
For this job, we particularly welcome applications from underrepresented groups and we also welcome applications for flexible working arrangements.
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Contact Person : Prof. Alex Shenfield Contact Number : 0114 225 6868 Date Advertised : 27-Sep-2024 Closing Date : 20-Oct-2024 Employment Type : Fixed Term - Full Time Location : City Campus Job number : 107905