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PhD Studentship: Combining Deep Learning and Computational Thermodynamics Modelling to Design Novel Functionally Graded Multimaterial Components
5 months ago
Supervisory Team: Professor Pedro Rivera and Dr Andrew Hamilton
Project Description:
Metal powder-based additive manufacturing is an emerging 3D printing technology that provides great topological freedom, allowing for component shapes unattainable via wrought technologies. However, the majority of the metal 3D printing has been on alloys designed for wrought conditions, and recent years have seen the emergence of alloy design efforts tailored specifically to this manufacturing technology, where extreme cyclic cooling and heating rates are present.
An additional breakthrough in metal 3D printing can be achieved by combining powder metals of distinct properties, such as heat resistance with low density, or corrosion resistance with ultra-high strength. The number of combinations is seemingly infinite, this requires a multiple approach combining computational thermodynamics and deep learning.
This PhD project will lead to the conception of functionally graded advanced components combining properties that are considered unattainable. The ideal candidate will have a solid background in deep learning methods and an understanding of solid state physics, and particularly the thermodynamics of alloys.
The work will be carried out in an international context, with collaboration with Kassel University (Germany) to perform builds and advanced characterisation down to the individual atom scale, and with the National Institute for Standards and Technology (NIST, USA) in data intensive methods analysis.
The key output of this project will be to find a range of novel functionally graded systems to satisfy emerging industries such as hydrogen storage and turbines, fusion energy, and space.
Entry Requirements
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).
Closing Date: 31 August 2024. Applications will be considered in the order that they are received, the position will be considered filled when a suitable candidate has been identified.
Funding: We offer a range of funding opportunities for both UK and international students, including Bursaries and Scholarships. For more information please visit PhD Scholarships | Doctoral College | University of Southampton. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
How To Apply
Apply online: HERE Select programme type (Research), 2024/25, Faculty of Engineering and Physical Sciences, next page select "PhD Engineering & Environment (Full time)". In Section 2 of the application form you should insert the name of the supervisor Pedro Rivera
Applications should include:
Research Proposal
Curriculum Vitae
Two reference letters
Degree Transcripts/Certificates to date
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees' well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
We offer a range of funding opportunities for both UK and international students, including Bursaries and Scholarships
