Research Fellow in Machine Learning for Construction
Faculty of Engineering and Environment

Applications are invited for a Research Fellow in Machine Learning for Construction to contribute to an exciting industry-led project for the development of an “AI-driven and real-time command and control centre for site equipment in infrastructure projects”. This project follows a successfully completed feasibility project hat tested the concept of improving site equipment in through the application IoT, AI, and BIM.  This position is funded by Innovate UK and you will work with a leading team of academics and award-winning digital construction businesses.  

As a successful candidate, you will lead the development and the implementation of machine learning and data analytics capabilities of the platform. In particular, you will implement AI techniques for the estimation of the productivity of site equipment, development of predictive schedules, and generation of benchmark data for earthwork.  

The ideal candidate will have experience in developing data pipelines within cloud-based platforms such as AWS, Google Cloud or Azure, particularly in the area of IoT, scalable database design, data processing and machine learning. Experience in developing machine learning applications using high level programming languages such as Tensorflow, Python and R within open-source platforms such as Jupyter or Conda is essential.

For an informal discussion about the post, please contact Assoc. Prof Dr. Mohamad Kassem by e-mail mohamad.kassem@northumbria.ac.uk

To apply for this vacancy please click 'Apply Now', and submit a Covering Letter and your CV, including a full list of publications where relevant and any documents specifically requested in the Role Description and Person Specification, such as a sample of written work or journal article. 

Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community. The University holds an Athena SWAN Bronze award in recognition of our commitment to improving employment practices for the advancement of gender equality and is a member of the Euraxess network, which delivers information and support to professional researchers.

Please note this vacancy will close on 08/03/2020