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Research Fellow position at Brunel University London

Call for applications: Research Fellow position at Brunel University London

Brunel University London is currently hiring for a Research Fellow position in the College of Engineering, Design & Physical Sciences, Department of Computer Science.
The ideal candidate will have expertise in one or more of the following fields:

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

Full-time, fixed-term for 14 months

Grade R1: £37,841 to £41,100 inclusive of London Weighting
Potential to progress to £44,663 per annum inclusive of London Weighting

Closing Date: 24/02/2023
Ref No: 3645


Brunel University London is a leading technology university with a rich history, dating back to 1966. Over the years, the university has established a strong reputation for its multidisciplinary research approach and its commitment to delivering economic, social, and cultural benefits to society. With a focus on cutting-edge research, Brunel has made significant contributions to numerous fields including computer science, engineering, and physical sciences. The university has consistently been ranked among the top universities in the UK for its research impact and its dedication to fostering innovation and progress. The university has a diverse research portfolio, covering a wide range of topics, from developing smart platforms for the Industrial Internet of Things (IIoT) to advancing the mining industry towards sustainable resource utilization. Brunel’s research has had a far-reaching impact, helping to tackle some of the world’s biggest challenges and making a real difference in people’s lives. The project, funded by the EU, aims to revolutionize the mining industry by promoting sustainable resource utilization and prioritizing the health and well-being of both people and the environment.

The objective is to create a cutting-edge platform for the Industrial Internet of Things (IIoT) that integrates both cyber and physical systems to improve the efficiency and sustainability of mining operations.

The platform will be designed to gather data from multiple levels of sensors including human, assets and environmental, as well as incorporating real-time market and historical data.

This project will not only bring innovative solutions to the mining sector but also help tackle future challenges related to standards and legislation in the extractive industry. The successful implementation of this project will bring numerous economic, social, and cultural benefits and contribute to the advancement of the mining industry towards a more sustainable future.

Job Description

Selected applicants will be joining the Intelligent Data Analysis (IDA) group in the Department of Computer Science at the university and will collaborate with colleagues from the Institute of Environment, Health and Societies.

The main focus of this position is the development of:

  • A software package that includes algorithms for detecting, classifying, and predicting events or failures, as well as dealing with bad data that may result from communication issues.
  • A scheduling tool that uses the “phase-wise, constrained, many-objective optimization” concept, derived from mining operation practices, to optimize the planning of mining operations.

The successful candidate will be part of a large and highly successful research team in the IDA group, who are pioneers in providing new solutions that meet the needs for safety, efficiency, and sustainability in the mining industry. They will bring innovative and competitive solutions to the mining business, tackle future challenges related to standards and legislation, and share their knowledge with as many sectors of the European extractive industry as possible.


  • PhD level education in related fields such as Machine Learning, Intelligent Data Analytics, Many-Objective Optimization, Statistics Analysis, Control Engineering, Fault Diagnosis, and Electrical and Electronics Engineering (other relevant areas will be considered).
  • Strong computing, analytical, and engineering skills supported by previous activities and responsibilities.
  • Ability to think innovatively and produce solutions that will be tested at multiple sites in the UK and EU.
  • Experience in related industries is a plus but not required.
Key Skills:
  • Software programming in languages such as Python, C, C++, C#, .NET, or Java.
  • Proficiency in machine learning algorithms, particularly deep learning.
  • Knowledge of many-objective optimization.
  • Familiarity with statistics software packages.
  • Understanding of the Internet of Things.
  • Experience in data-based fault detection/diagnosis.

The project will be supervised by academic staff including Prof. Zidong Wang, Prof. Xiaohui Liu, and Dr. Stasha Lauria and will involve conducting a full cycle of research and development from concept to implementation.

For additional details about the position and how to apply, visit

Find more opportunities HERE.

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