2 PhD Opportunities at UNSW Sydney

The Scientia PhD program has announced its projects for 2018.  There is over 100 projects on offer in all areas of research. I’m bringing to your attention 2 in the water/coastal space.  We are currently recruiting for high quality students in 2 very different fields. Both ads are below. Scientia scholars will have a strong commitment to making a difference in the world with demonstrated potential for contributing to the social engagement and/or global impact pillars of the UNSW 2025 Strategy. To be eligible students must have research experience including a first class honours degree or a masters of research. Women and Indigenous scholars are encouraged to apply.

 

The scholarship scheme offers the following unique aspects:

$40K a year stipend for four years

Tuition fees covered for the full 4 year period

Coaching and mentoring will form a critical part of your highly personalised leadership development plan

Up to $10k each year to build your career and support your international research collaborations

 

Project 1: Novel Remote Sensing Applications of Artificial Intelligence to Understand Changing Coasts

 Supervisors: Dr. Kristen Splinter (UNSW Sydney); Professor Ian Turner (UNSW Sydney) and Dr. Meg Palmsten (NRL).  

We are seeking exceptional candidates with an interest in Coastal Engineering and Science and a strong background/keen interest in machine learning techniques. The successful applicant will be based at the Water Research Laboratory on Sydney’s Northern Beaches (www.wrl.unsw.edu.au) and be part of the wider group of international researchers involved in coastal imaging (see https://www.linkedin.com/groups/12010767). The International Coastal Observing Network (ICON) initiative involves a suite of data that has been collected around the world in the past 3 decades from such locations as Australia, the US, and Europe. The successful candidate will be encouraged to develop a research plan to spend time at these sites and collaborating with international researchers. 

State-of-the-art machine learning algorithms recently developed in fields of computer science are at a very early stage of application to coastal remote sensing data sets. Via the newly-established ICON initiative, extensive video-based data sets collected around the world over the past 3 decades present a unique and novel opportunity to explore new research applications of machine learning. Results will ultimately better inform coastal scientists, engineers and managers about the temporal variability of the world’s coastlines and how coastlines are adjusting to climate change. Through the ICON network, this project aims to deliver unprecedented new insight to explore how sandy coastlines can be anticipated to change in to the future.

http://www.2025.unsw.edu.au/apply/scientia-phd-scholarships/novel-remote-sensing-applications-artificial-intelligence-understand

  

Project 2: Achieving Fair and Collective Adaptation to Sea-Level Rise

Supervisors: Dr Sonia Graham (sonia.graham@unsw.edu.au), Professor Marc Williams, Dr Kristen Splinter

Sea-level rise, coastal migration and more intense extreme weather events will render 350 million people vulnerable to coastal flooding by 2050. It is in the interests of coastal communities to adapt to such environmental change, yet little is known about how collective adaptation is achieved and whether local initiatives are socially just. This project will advance our understanding about collective action and climate justice through three international sea-level rise case studies. The ultimate aim is to ensure that future coastal adaptation is fair and collaborative to sustain coastal communities through climate change.

For more information go to: https://www.2025.unsw.edu.au/apply/scientia-phd-scholarships/achieving-fair-and-collective-adaptation-sea-level-rise

FAQ: https://www.2025.unsw.edu.au/apply/unsw-scientia-phd-scholarships-faqs

Guidelines: https://www.2025.unsw.edu.au/apply/node/69/

 

Interested applicants MUST apply online via the link on the project page