Research Associate in Computer Science

This is a fixed term contract until 31/07/2023, full-time and part- time positions available

The Department of Computer Science resides within the School of Science and Technology on the Clifton Campus, and there are excellent collaborative opportunities with colleagues in other departments and research centres. Currently, the department comprises 60 academic staff and ~20 PhD research students, as well as large undergraduate and taught postgraduate cohorts. The department provides researchers with an exciting environment for undertaking high-quality, interdisciplinary work.

Whether you are seeking a full-time or part-time position, we welcome applications from all interested candidates. If you are interested in joining any of the above projects, please submit your application, including a cover letter outlining your relevant experiences and specify the project you prefer to work on.

About the roles

We are specifically looking for Research Associates in Computer Science to work on one of the following research projects conducted at the Department of Computer Science:

FPGA and High Performance Computing - This project requires expert knowledge in VHDL and electronic design for FPGA’s. This project aims to provide language(s), compilers, middleware and support services to leverage an FPGA cluster for both research and commercial use. You will be working on electronic and VHDL representations to support specialised systems for controlling a 300+ FPGA cluster. For more details about this project, please contact Dr Jon Robinson.
Cybersecurity and Cyber Physical Systems - The duties include the design and development of a proactive model for automated authentication and verification of embedded physical systems for securing critical national infrastructure (CNI). The project will first aim to design a cyber-physical proactive authentication and verification protocol for CNI. Second, it will look at the modelling and development of a trustworthy AI approach to proactively identify potential threats on the CNI and set the right intervention plan. The project will focus on utilising the developed proactive authentication and verification protocol with the involvement of some of the physical aspects from the connected smart things within the CNI. For more details about this project, please contact Dr Ali Sadiq.
Machine Learning / Artificial Intelligence - This project aims to use non-invasive sensors, including wearables, to predict and monitor the behaviours and emotions of individuals, including vulnerable groups. It will explore the use of AI/ML algorithms and multivariate sensor fusion to improve healthcare systems and enhance the lives of targeted groups. This project will seek to develop correlation maps to inform interventions and care by linking signals to behavioural patterns, stress levels, and emotions. For more details about this project, please contact Dr Kennedy Isibor.
Internet of Things and Activity Recognition - This project aims to develop a digital twin prototype for a smart living environment (DIGIHOME) that will support the incorporation of IoT sensing devices and machine learning models for activity recognition and monitoring. Additionally, the project will also develop a framework for integrating DIGIHOME with relevant digital twin software-as-a-service platforms and the development of a model for data fusion and validation. For more details about this project, please contact Dr Salisu Yahaya.
Analysis of Video Data and Computer Vision - The successful candidate will work as part of a team and will be required to carry out inspection and analysis of video modifications in the compressed domain, in particular videos encoded using the H.265/HEVC standards. The aim of this project is to propose and develop STEGtify: a tool that can detect hidden messages in videos, which will aim to prevent the transmission of malicious content through online and offline videos. For more details about this project, please contact Dr Ismahane Cheheb.
Abnormal Behaviour Detection - The project aims to develop a novel AI-enabled health monitoring scheme to support older adults’ independent living and emergency reactions. One of the main challenges in deploying such systems is the uncertainty of confirming the degree of importance of the detected abnormal human behaviours, e.g., human fall, that requires urgent responses post the abnormal human behaviour detection. For more details about this project, please contact Dr Abdallah Naser.
Augmented Reality Technologies in Surgical Healthcare - This study aims to investigate how Augmented Reality (AR) is transforming the healthcare industry and enabling more effective surgical procedures and better patient outcomes. The project will deliver mechanisms and tools for designing effective real time visual feedback and AR experiences to support spinal surgical procedures and patient education. For more details about this project, please contact Dr Temitope Alade.

Please review the online information about the post on www.ntu.ac.uk/vacancies .

If you have any specific queries in relation to this position that the online information does not cover, then please contact:

Prof. Ahmad Lotfi, Head of Department of Computer Science, via [email protected]

About NTU

NTU prides itself on being an inclusive employer. We value and celebrate equality in opportunities, and we welcome applications from people who reflect the diversity of our communities.

This role does not meet the minimum requirements set by UK Visas & Immigration to enable sponsorship of migrant workers. Therefore, we cannot progress applications from candidates who require sponsorship to work in the UK. Please ensure that you have the appropriate right to work in the UK for this role and consult the Home Office website for further information.

Please note that this role is covered by the Rehabilitation of Offenders Act (1974) and successful applicants will be asked to declare any unspent criminal convictions.

Post Jobs Online Apply Job