西澳大学PhD in Digital Engineering for Energy Infrastructure Transformation申请条件要求-申请方
主办方
西澳大学
PhD直招介绍
TIDE invites two exceptional individuals to join our collaborative, industry-driven research program. Unlock your potential and contribute to data and physics-based science to better understand offshore energy environments and improve future infrastructure design and operation.
Cluster A - Aerial remote sensing of ocean currents
The project aims to develop, deploy and analyse data from a new instrument for sensing ocean currents from the air. The instrument is based on directly georeferenced optical and thermal imagery, and will integrate various off-the-shelf industrial- and science-grade instruments. While similar systems are being developed worldwide, there are yet no affordable and reliable systems in use operationally. The modular design would be unique by being deployable on both manned and unmanned vehicles.
The PhD student would work alongside a postdoctoral researcher who is leading the development of the instrument, algorithms, and their application to oceanography. The candidate would contribute to the hardware development and conduct aerial surveys in regional locations. They will also contribute to oceanographic experiments including a 35-day cruise on CSIRO’s research vessel Investigator, where the candidate will be supported by an experienced UWA-CSIRO field team. They will also develop algorithms and conduct their own submesoscale ocean flow research.
Cluster B – Machine Learning methods to correct spectral ocean wave forecasts
Numerical weather forecasts are classically produced using physics-based numerical models that, in some instances, assimilate sparse observations. Errors in these numerical forecasts can arise from many different sources, including incomplete physics, the choice of the data assimilation algorithm, initial and boundary conditions, and model numerics. Similar to many numerical forecasts, ocean wave forecasts are computed on a large spatial grid for computational efficiency.
Evaluation of numerical wave forecasts, using in situ buoy measurements, reveals models can perform poorly in site-specific areas. However, the buoy dataset used for comparison also constitutes an opportunity to learn site-specific corrections. Also, a machine learning model would naturally allow the use of any contextual variables which is not always possible using a physics-based wave model. The main goal of the thesis is to design a machine learning based correction of the wave forecast using historical wave buoy measurements and relevant contextual variables (e.g. tides, currents, wind).
Invest in Your Future
As a PhD candidate in TIDE, you work with a large, international, multi-disciplinary group that has a strong focus on research excellence and on delivering real impact for our industry partners.
西澳大学 PhD in Digital Engineering for Energy Infrastructure Transformation项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
Successful applicants will be invited to apply for a $42,000 per year scholarship through the UWA online portal. Visit the Graduate Research School for more information.
西澳大学Phd申请条件和要求都有哪些？PhD in Digital Engineering for Energy Infrastructure Transformation项目是不是全奖？有没有奖学金？下面我们一起看一下西澳大学申请Phd直招需要具备哪些条件和要求，以及托福、雅思语言成绩要到多少才能申请。
申请要求
The candidate should have a qualification and skills in physical oceanography, engineering or similar discipline. A strong numerical background is essential, as is a willingness to conduct fieldwork in remote locations and learn low-level electronics.
报名方式
招生人信息
Kath Lundy
邮箱：tide@uwa.edu.au
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