PhD Position in Industrial Artificial Intelligence: Algorithms for predictive maintenance of vehicles in a connected environment

In collaboration with City, University of London, the School of Mathematics, Computer Science & Engineering, and Bosch Automotive Service Solutions Ltd, EIT Digital Doctoral School is offering a PhD studentship. The studentship falls under the new EIT Digital Industrial Artificial Intelligence Doctoral Programme at City, University of London. The studentship consists of a full fee waiver and a stipend of £18K per year, for four years. As part of their studies and training, students will spend time at City, University of London, EIT Digital London Co-Location Centre and Bosch workshop in Stockport (Greater Manchester). In addition, over the 4 years of study, the PhD will spend between 3 and 6 months abroad to enrich their research experience, for which a supplementary budget is available. EIT Digital also provides a European training in innovation, entrepreneurship and digital transformation leadership at other EIT Digital centres across the EU.

The PhD project, entitled “Algorithms for predictive maintenance of vehicles in a connected environment”, is focused on developing novel AI algorithms for predicting and specifying repair and maintenance requirements of vehicles in connected environments, where the vehicle and the repair workshop are in two-way data communication with cloud-based services. These may include algorithms for identifying what data to collect, identifying and predicting faults using collected data, advising vehicle operators of repair and maintenance requirements and optimising the repair and maintenance tasks to be performed.

The appointed candidate will have a degree and a MSc in Computer Science or an area related to Artificial Intelligence and cloud computing. Given the nature of the project, experience in industry is advisable.

Applications, consisting of a CV and a Personal Statement, should be submitted to EIT Digital Doctoral School Office at Closing date: 17:00 BST, 15 September 2019. 

Interviews are scheduled for the week commencing the 23 September 2019.

The role is available from 15 October 2019 or earlier by negotiation.

For further information about the post please contact

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