High Performance Visualisation Workflows for The Creative Use of BigData in Environmental Geohazards

Big data is routinely generated e.g. in modern astrophysical sky surveys and
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). Further, satellite data such as that
acquired by ESA’s Sentinel-2 mission can offer an exciting wealth of new
information capturing natural colour of 10 m resolution of every landmass on
the globe every five days. 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 or validating
complex theoretical models in cosmology. Creative uses of such big data (e.g.
through high performance visualisation) that are fully integrated in virtual /
augmented reality environments often require execution of lengthy, and hard
to scale data pipelines. Emerging technologies for high performance
visualisation can provide outstanding aids for 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 visual
tools for applied geoscientists. Similar benefits are envisaged to apply also to
the field of cosmology.

The overarching aim of the project is to design and implement appropriate
algorithms and interfaces fully exploiting the capabilities of emerging and
future technologies in realising visual computing services to support
execution of high performance processing pipelines for virtual and
augmented reality applications, thus building capacity and home-grown
expertise on sophisticated visualisation tools underpinning creative
technologies. The project will also make the case for applicability of the
outcomes to domains outside geohazards through knowledge transfer
activities of developed algorithms and tools to other disciplines such as
cosmology. We will build upon our previously developed cloud-based
visualisation solutions for multi-dimensional 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.

Candidate specification:
Applicants will have a good first degree (minimum 2.1 or equivalent) in computer games, computer
animation, computing or a related subject, with a strong interest in high performance computer
graphics and visualisation. The successful candidate will also have experience of some or all of: Virtual
/ Augmented Reality, Game Engine Programming and Distributed Infrastructures. A good
understanding of point clouds, and good programming skills are essential, and cross-platform
experience, especially relating to code optimisation and parallelisation using C++, Python, CUDA and
OpenCL.

How to apply:
We welcome applications from highly motivated prospective students who are committed to develop outstanding research outcomes. You can apply online at www.port.ac.uk/applyonline. Please quote project code CCTS4350218 in your application form

Applications should include:
- a full CV including personal details, qualifications, educational history and, where applicable, any employment or other experience relevant to the application
- contact details for two referees able to comment on your academic performance
- a research proposal of 1,000 words outlining the main features of a research design you would propose to meet the stated objectives, identifying the challenges this project might present and discussing how the work will build on or challenge existing research in the above field.
- proof of English language proficiency (for EU and international students)

All the above must be submitted by the 11th of February 2018.