Postdoctoral Research Assistant in ‘Data-driven Models for Offshore Monopile Design’’

We are seeking a full-time Postdoctoral Research Assistant to join the Oxford Civil and Offshore Engineering Research Group at the Department of Engineering Science in central Oxford).  The post is funded by industry (Ørsted) and is fixed-term for 12 months.

The role is concerned with developing and exploiting new data-driven modelling techniques for the analysis and design of offshore foundations for wind turbine support structures. The research to be conducted will contribute to a wider project – funded by industry – on the development of new design procedures for offshore monopile foundations.

You will be responsible for:

•    Liaising with the industry partner (Ørsted) to facilitate knowledge transfer relating to the data-driven 1D modelling procedures for offshore monopile design that have been recently developed at Oxford University.

•    Further development of 1D data-driven methods for offshore monopile design, including applications at chalk sites

•    Contributing to the development and interpretation of medium-scale field tests on lateral loaded piles to be conducted at a site in Cuxhaven, Germany

You should possess a PhD or DPhil (or close to completion)in a research area related to the role. You should also have experience in developing data-driven models for offshore monopile design. 

Informal enquiries may be addressed to Prof. Harvey Burd (email: [email protected])

For more information about working at the Department, see

www.eng.ox.ac.uk/about/work-with-us/

Only online applications received before midday on 20th February 2024 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.

The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology. 

Keywords

Offshore, Geotechnics, Foundations, Monopiles, Data-driven models