Research Assistant

University of the West of Scotland – School of Computing, Engineering & Physical Sciences

Paisley Campus

Full time: 35 hours per week

Fixed term: 24 months

You will join a dedicated team who strive to continuously inspire our students and wider University community – and, through modern teaching and impactful research, continue to deliver innovative solutions to some of the world’s biggest challenges.

Join the groundbreaking WEATHER project led by the University of the West of Scotland (UWS), in collaboration with University of KwaZulu-Natal (UKZN), the RCSI Faculty of Nursing and Midwifery, and University of Portsmouth, funded by the National Institute for Health and Care Research (NIHR). The project aims to develop a predictive warning system intervention (PWSi) designed to mitigate risks linked with Extreme Weather Events (EWEs) in KwaZulu-Natal, South Africa. Leveraging telecommunication networks, particularly 5G networks, the system will deliver timely warning alerts to communities, enabling proactive response measures and reducing the potential impact of EWEs. The project will involve working with international research groups and projects, working with other researchers and PHD students with access to professional training.

As a Research Assistant, you will play a vital role in the research project focused on predicting the outbreak of disease linked to extreme weather events through mathematical modeling and data-driven AI algorithms. Working under the guidance of Professor Muhammad Zeeshan Shakir, Director of UWS Digital Connectivity and Innovation for Sustainable Futures, you will contribute to the design and development of predictive models using environmental data and health informatics. Your responsibilities will include conducting research, producing high quality research papers, analyzing data, and collaborating with research teams from collaborating institutions to advance our understanding of the relationship between extreme weather events and disease outbreaks. This role offers an exciting opportunity to contribute to cutting-edge research aimed at addressing challenges in public health and sustainability.

The successful candidate should have the following:

• MSc or equivalent in in Electrical/Electronic Engineering or Computer Engineering/Science or Mathematics or related areas.
• Experience in development of AI/Machine learning algorithms with proven track record in using machine learning and artificial intelligence software libraries (e.g., Scikit-learn, TensorFlow, Keras).
• Experience in technical writing (research publications) and preparation of reports.
• Strong analytical and problem-solving skills.
• Proficiency in programming languages (e.g., Python, Java, C/C++, MATLAB).

About us

University of the West of Scotland is one of Scotland’s largest and most modern universities. Our reach across the country, together with our London campus, means that UWS is a significant force in global knowledge creation, innovation, and a leading provider of undergraduate, postgraduate and research degree education. Our degrees provide students with a transformational experience; equipping them with highly sought-after graduate skills that set them up for global success in world-leading sectors, industries and businesses.

With cutting-edge courses, modern pedagogy and practical knowledge, we enable our students and staff to experience the joy of learning, teaching, research and innovation, and apply their knowledge for the benefit of others.

UWS is officially ranked by Times Higher Education in the top 200 universities worldwide under 50 years old (2023 Young University Rankings).

The School of Computing, Engineering & Physical Sciences offers industry-focussed teaching and research opportunities that deliver solutions to real-world problems. You will join an innovative and supportive team, playing a key role in driving forward our ambition to deliver transformational change, through outputs that have a tangible, early and positive impact on society across the globe. Our students benefit from state-of-the-art facilities, extensive expertise in research and development, and our robust collaborations with multinational companies across the world.

About UWS DCISF:

Digital Connectivity & Innovation for Sustainable Futures (DCISF), an integral research group within Artificial Intelligence Visual Communications and Network Research Institute, stands at the forefront of digital innovation. With substantial funding from prestigious entities such as NIHR, QNRF, EU programs, UK and Scottish Governments, British Council, and Innovate UK, our group has spearheaded groundbreaking research and received recognition through numerous awards. Among our accolades are the Fred W. Ellersick Award in 2021, Innovate UK Award of Excellence in 2023 and 2018, and several best research paper awards.

At DCISF, our vision is clear: to revolutionize automation for a sustainable future. We are committed to pioneering digital connectivity solutions that are reliable, robust, and resilient, while simultaneously driving innovations that enhance efficiency, minimise environmental impact, and elevate overall quality of life.

Our strategy is built upon three pillars. Firstly, we prioritize nurturing research and development through access to state-of-the-art facilities such as our 5G and IoT Testbeds. Secondly, we emphasise the importance of delivering impactful Knowledge Exchange Partnerships, engaging in KTP projects, and fostering industry collaborations to drive real-world applications of our research. Lastly, we are dedicated to producing high-quality personnel, supporting the development of digital skills among PhD candidates and Early Career Researchers (ECRs), ensuring a pipeline of talent equipped to tackle the challenges of tomorrow.

Aligned with our vision and strategy, our research themes encompass Digital Connectivity, Health and Wellbeing, and Climate Change. Through these themes, we strive to address pressing societal issues and contribute to the advancement of knowledge and innovation in our field.

UWS is fully committed to the UK Concordat to support the Career Development of Researchers which sets out clear standards that research staff can expect from the University. It aims to improve the employment and support for research careers in the UK and provides a framework for career development based around the Concordat principles.

We offer our staff a caring and supportive environment, across five campuses, and a competitive benefits package which includes:

• 35 days of annual leave, plus a further 12 days for public/university holidays
• Additional days leave on your birthday.
• Defined benefit contribution pension scheme (currently 23%), including death in service benefits upon joining the scheme.
• A flexible approach to working pattern and work-life balance.
• Employee discount scheme across 3,500 retailers
• Fitness facilities across our campuses
• Access to a range of health and wellbeing resources, including occupational health, physiotherapy and access to our Employee Assistance Programme
• Professional, career and research development opportunities.

Informal queries can be sent to Muhammad.shakit@uws.ac.uk however applicants must apply online and submit 2 page resume as an attachment detailing your educational background, previous research projects/experience.

Please register your interest if you would guidance on how to submit a formal application to jobs@uws.ac.uk by the 17^th May. Professor Muhammad Shakir will hold an information session via Teams.

Interview date: Week commencing 5^th August 2024

The University reserves the right to shorten/extend the closing date of any position where a high/low volume of suitable applications are received. Therefore, if you are interested in this role, an early application would be encouraged.

UWS is committed to equality and diversity and welcomes applications from underrepresented groups.

UWS is a “Disability Confident” employer.

University of the West of Scotland is a registered Scottish charity, no. SC002520.