Durham University is currently recruiting for three Energy PhD posts to support its work in Offshore Renewable Energy and Offshore Wind Energy.
Full details, including deadlines dates for applications, are available below. Applications can be made online at: https://www.dur.ac.uk/postgraduate/study/apply/
Vacancy for Collaborative PhD with Offshore Renewable Energy (ORE) Catapult
A PhD studentship is available for research into offshore investment planning under severe uncertainty, at the School of Engineering & Computing Sciences, and the Department Mathematical Sciences, Durham University. Support and active involvement will come from the Offshore Renewable Energy (ORE) Catapult, which has facilities in Blyth, Glasgow and Fife.
The aim of the project is to investigate investment planning over a wide range of technology options by formulating a set of decision problems taking into account severe uncertainties in both operational and environmental data. The potential candidate will have a good degree (normally first class or equivalent) undergraduate or MSc degree in Engineering, Mathematics, or Statistics. A good background in Statistics is required.
For more information about this opportunity please do not hesitate to contact Dr B Kazemtabrizi ([email protected]), or Dr M Troffaes ([email protected]) as soon as possible and preferably before 23rd September 2016. Proposed start date is 1st October 2016 but there is flexibility.
For further information about this opportunity go to http://www.jobs.ac.uk/job/AON868/phd-studentship-offshore-transmission-systems-asset-management-under-severe-uncertainty/
Vacancy for 2 PhD studentships in Data Mining Wind Farm Operational and Maintenance data funded through DONG Energy
Off shore wind energy is one of the fastest growing sectors, with major new projects planned within European waters as well as further afield. These new wind farm developments are sited further off shore than ever before (the Round 3 wind farm projects in the North Sea are some 200km off shore).
This presents new challenges in terms of maintenance and repair: the cost of going on site is significantly greater (both financially and time).
These two linked PhD projects will develop novel data mining methods to maximise the information gathered from wind turbines’ sensor arrays. The aim is to be able to identify that a wind turbine is developing a fault well in advance of that fault becoming sufficiently severe that it prevents the wind turbine from operating. Given this advanced warning, a wind farm operator is then able to organise maintenance and identify a good weather window to carry that maintenance out.
These projects will be undertaken with close collaboration with DONG Energy (Danish Oil and Natural Gas, one of the largest wind farm operators globally).
These PhD studentships are available to Home and EU students. Please contact Dr Peter Matthews ([email protected]) for further information preferably before 30th September.
For further information go to https://www.findaphd.com/search/ProjectDetails.aspx?PJID=73802&LID=427
Durham University’s online application link can be found at https://www.dur.ac.uk/postgraduate/study/apply/