Research Fellow - 13589

Full time, Fixed-term for 14 months

Brunel University London was established in 1966 and is a leading multidisciplinary research-intensive technology University.

Applications are invited for a Research Fellow position with specialisation in one or more of the following areas:

• Machine Learning
• Intelligent Data Analytics
• Many-Objective Optimisation
• Statistics Analysis
• Control Engineering
• Fault Diagnosis
• Electrical and Electronics Engineering

The successful applicant will join the Intelligent Data Analysis (IDA) group in the Department of Computer Science and work closely with colleagues whose research is linked to the Institute of Environment, Health and Societies. This exciting EU funded project addresses the needs of the mining industry to move forward towards a sustainable use of resources while keeping people and environment at the forefront of their priorities. This project aims to develop a smart Industrial Internet of Things platform that will improve the efficiency and sustainability of mining operations by connecting cyber and physical systems.

The platform will collect data from sensors at 3 levels:

1. human,
2. assets,
3. environment, and will also incorporate both market real time and historical data.

The focus of this post is on the development of:

1. a software package consisting of a set of efficient algorithms for detecting, classifying and predicting the events/failures as well as handling bad data resulting from communication constraints; and
2. a smart scheduling tool for optimal planning of mining operations based on the “phase-wise, constrained, many-objective optimization” concept, which stems from mine operation practice.

The successful candidate will become part of a large and highly successful research team in the IDA group who will be the pioneers in providing new solutions addressing the needs for safety, efficiency and sustainability, bringing innovative and competitive solutions to the mining business, facing future challenges regarding standards and legislation, and spreading the knowledge to as many sectors of the European extractive industry as possible.

Applicants will be required to demonstrate their ability to think innovatively and produce solutions that will be applied and tested in multiple sites throughout UK and EU. The project will require you to take a concept and conduct a full cycle of research and development under supervision from academic staff.

Your educational background should be at PhD level in related areas such as Machine Learning, Intelligent Data Analytics, Many-Objective Optimisation, Statistics Analysis, Control Engineering, Fault Diagnosis, and Electrical and Electronics Engineering. Other relevant areas will also be considered. Previous industrial experience and/or national or international scientific awards is important.

This position requires strong computing, analytical and engineering skills supported by evidence of your previous activities and responsibilities.

The key skills required:

• Software programming (Python, C, C++, C#, .NET or Java);
• Machine learning algorithms especially deep learning;
• Many-objective optimisation;
• Statistics software packages;
• Internet of Things;
• Data-based fault detection/diagnosis.

Experience in related industries is highly desirable and advantageous, but not essential for the post.

For further information please contact Professor Savvas Tassou, E-mail: savvas.tassou@brunel.ac.uk, Professor Zidong Wang at Zidong.Wang@brunel.ac.uk.

Closing date for applications: 24 February 2023.

For further details about the post including the Job Description and Person Specification and to apply please visit https://careers.brunel.ac.uk

If you have any technical issues please contact us at: hrsystems@brunel.ac.uk

Brunel University London is fully committed to creating and sustaining a fully inclusive workforce culture. We welcome applicants from all backgrounds and communities, we particularly welcome applicants who are currently under- represented in our workforce.

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