3 years- PhD Studentship in Intelligent Big Data Analytics for Safer Ship Navigation in the Arctic Environment
University of Southampton’s School of Electronics and Computer Science
United Kingdom

3 years- PhD Studentship – Intelligent Big Data Analytics for Safer Ship Navigation in the Arctic Environment


Electronics & Computer Science


Location: Highfield Campus


Closing Date: Sunday 30 September 2018


Reference: 975918FP


While the Arctic is an extremely harsh environment, the effects of climate change and global warming are reducing its extent of sea ice very rapidly, therefore transforming it into a navigable ocean. Nevertheless, only few cargo ships navigated the northern shipping routes in recent years. In particular, substantial savings in voyage times and fuel consumption can be made in the future if the Arctic routes become safer to be taken on. The voyage time, under such case can be around 22 days from China to Europe, when compared to 35 days via Singapore and the Suez Canal; or 46 days around the African continent via South Africa. Nevertheless, the Arctic remains a harsh environment with its highly complex and variable ice cover and ice build-up on board vessels, notwithstanding its changing wave climate.

 

Following the above, and in order for the maritime industries to realise the international economic benefits of Arctic shipping, one would require new transformational technological approaches for supporting safety of shipping in the Arctic. One should provide integrated solutions for assuring safety of ship navigation in the Arctic region.

 

In this research programme, one particularly focuses on advancing big data research, for achieving computer machine intelligent knowledge discovery and critical decision-support which assures real-time Safer ship navigation with Optimized ship voyages and fuel consumption. Machine learning, deep mining and intelligent semantics reasoning for building Augmented Situation Awareness will be investigated in this PhD study. Satellite and in situ observations from the UK Met Office will be acquired for data fusion with voyage and fuel consumption optimisation models with controlled geospatial uncertainties. These will be be captured in real-time in order to advance safety of Arctic shipping.

 

Experience in python and/or java programing is essential. Skills in semantic modelling, machine learning and software system design principles will be required. Knowledge of Hadoop, Spark and DOCKER technologies, R and OWL programming languages are also desirable.This research will be conducted under a joint collaboration between IT Innovation Centre, Department of Electronics and Computer Science and the Ship Science Group. It offers a unique opportunity for the candidate to interact with these two research groups across faculties at the University of Southampton.

 

The successful candidate will join our research team in the ongoing SEDNA project (https://sedna-project.eu/)

 

Applicants for this position should apply to the PhD in Computer Science in Electronics and Computer Science using the online application form https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page

 

Please state clearly in the application that you are interested in the above studentship.

 

Supervisors: Dr Z. Sabeur and Professor A. Shenoi

 

For further information please contact Dr Zoheir Sabeur, University of Southampton IT Innovation Centre. Email address: zas@it-innovation.soton.ac.uk


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