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  Machine learning for more effective offshore energy operations


   N0MES CDT

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Prof Trung Thanh Nguyen  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The EPSRC Centre for Doctoral Training in Net Zero Maritime Energy solutions (N0MES) has a 4-year funded PhD place available for an exceptional researcher. With the support of the University of Liverpool (UoL), Liverpool John Moores University (LJMU) and 33 maritime energy sector partners, N0MES PGRs will pursue new, engineering-centred, interdisciplinary research to address four vital net zero challenges currently facing the North West, the UK and beyond:

a) Energy generation using maritime-based renewable energy (e.g. offshore wind, tidal, wave, floating solar, hydrogen, CCS);

b) Distributing energy from offshore to onshore, including port- and hinterland-side impacts and opportunities;

c) Addressing the short- and long-term environmental impacts of offshore and maritime

environment renewable energy generation, distribution and storage; and

d) Decommissioning and lifetime extension of existing energy and facilities.

The PhD Project

It is critical to improve the operational efficiency and emission of offshore operations, given that they are vital to the offshore wind energy industry and world’s Net Zero targets. This PhD project will revolutionise some parts of offshore operations by harnessing the power of cutting-edge artificial intelligence / machine learning techniques and untapped data sources, making these operations cleaner and more efficient. 

Successful candidates will work as a team with other PhD students in the same domain of machine learning and optimisation for maritime transport, under the supervision of a multidisciplinary supervision team comprising LJMU academics and industry experts from a global energy company. You will join the world-leading LOOM research-institute in an inclusive environment, collaborating with 40 other PhD/postdoc researchers. In addition, you will have the unique opportunity to undertake funded secondments to the industry partner to enhance your experience/network, access real-world applications, and gain career opportunities.

Click here for more information about the N0MES centre at LJMU, the LOOM research centre where the researcher will be hosted, and our research capability.

Applications

We want all of our staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances. For example, if you have a disability you may be entitled to a Disabled Students Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.

We believe everyone deserves an excellent education and encourage students from all backgrounds and personal circumstances to apply.

Important Application Process

Candidates wishing to apply should send your application to Prof. Trung Thanh Nguyen [Email Address Removed], with an email title “PhD scholarship in the N0MES CDT”. Please send the below: an up-to-date CV and a transcript,  and a supporting statement [maximum 300 words] detailing; what inspires you within this project, how your skill set matches the project, up to 3 examples showing your commitment to science, piece of science that excites you & anything else to support your application. 

Computer Science (8) Engineering (12)

Funding Notes

The EPSRC funded Studentship will cover full tuition fees of £4,786 per year and pay a maintenance grant for 4 years, starting at the UKRI minimum of £19,237 pa. for 2024-2025. The Studentship also comes with access to additional funding in the form of a research training support grant which is available to fund conference attendance, fieldwork, internships etc. 

EPSRC Studentships are available to any prospective student wishing to apply including international students. Up to 30% of our cohort can comprise of international students.


References

Applicant Eligibility
Candidates will have, or be due to obtain, a Master’s Degree or equivalent from a reputable University in relevant subject. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered.
The following expertise/experience will be required:
• Machine learning, large data handling/acquisition (e.g. via web APIs)
• Demonstrable experience in programming and data analytics.
Preferred, but not mandatory, experience in:
• Optimisation / computational intelligence
• Maritime transport/shipping
• Backend development
• Open source environments (Linux, Github etc.)
• Engagement with industry/external

Where will I study?


Project supervisors

Prof Trung Thanh Nguyen's profile is coming soon

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