Funding

Self-funded PhD students only

Project code

CCTS4480220

Department 

School of Creative Technologies

Start dates

and

Closing date

Applications accepted all year round

Applications are invited for a fully-funded 3 year PhD to commence October 2019 or February 2020.


The PhD will be based in the School of Creative Technologies, and will be supervised by Dr Mel Krokos.

Big data is routinely generated e.g. in the study and remediation of environmental geohazards such as landslides or volcanic ash dispersion. As an example, field-mapping needs to be supplemented by satellite imagery and data acquired from field-deployed Unmanned Aerial Vehicles (UAVs). Numerical simulations are also deployed to quantify impacts, e.g. in overcoming the shortcomings of eruption cloud models as demonstrated by the Icelandic eruption of 2010.

Emerging technologies for high performance visualisation can provide outstanding aids for (often near real time) data exploration and detailed insight into complex regions of interest to support scientific discovery. There is a need for innovative visualisation mechanisms, e.g. for processing complex pipelines from UAVs, making meaningful comparisons of ash cloud models or integrating with real world observations (historic or current). This project will develop an integrated visualisation toolkit, underpinned by emerging technologies, the first step towards a new generation of high capacity tools for applied geoscientists.

We will build upon our previously developed cloud-based visualisation solutions for multidimensional data analysis and knowledge discovery of a priori unknown patterns / relationships in multivariate and complex datasets. We will extend our previously developed algorithms for high performance rendering based on customised volume ray-casting to harness heterogeneous environments involving multi-core processors and GPUs, e.g. the University of Portsmouth SCIAMA supercomputer. Such high performance visualisation solutions have the future potential to underpin field-work activities via mobile, augmented reality applications.

This PhD will be in the School of Creative Technologies in the Faculty of Creative and Cultural Industries (CCI) and will involve a multidisciplinary supervisory team drawn from CCI and the Faculties of Science and Technology. The work will be undertaken in collaboration with a European network of renowned academic and research institutions from Italy, Spain, Greece, Hungary and Switzerland, and there will be potential opportunities for student work placements within these institutions.

Funding

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).

2019/2020 entry

Home/EU full-time students: £4,327 p/a*

Home/EU part-time students: £2,164 p/a*

International full-time students: £15,900 p/a*

International part-time students: £7,950 p/a*

*Fees are subject to annual increase

By Publication Fees 2019/2020

Members of staff: £1,610 p/a*

External candidates: £4,327 p/a*

 

*Fees are subject to annual increase

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in a relevant subject area. In exceptional cases, we may consider equivalent professional experience and/or Qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

How to apply

We’d encourage you to contact Dr Mel Krokos (mel.krokos@port.ac.uk) to discuss your interest before you apply, quoting the project title and project code (CCTS4480220).

When you are ready to apply, you can use our online application form and select ‘Computing and Creative Technologies’ as the subject area. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. 

Our ‘How to Apply’ page offers further guidance on the PhD application process.

Please note, to be considered for this funded PhD opportunity you must quote project code (CCTS4480220) when applying.

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