PhD Studentship: Development of data-driven design optimization framework for expensive real world engineering problems

Supervisory Team: Dr. Haris Moazam Sheikh

PhD Supervisor: Haris Moazam Sheikh

Project description:

Mechanical design is non-intuitive. Even with years of experience, the non-intuitive behaviour of physical systems, due to our limited understanding of them, can mean the optimal geometry is surprising or even extreme (look up, for instance, the bulbous bow of a ship). However, the expense of trying out novel designs is usually extremely prohibitive for real-world engineering problems restricting us to unadventurous design spaces. In addition, the geometric constraints and designer biases imposed by conventional methods can restrict the design process to a particular space and make non-intuitive designs impossible.

Data-driven methods have forced a major reconsideration of current research techniques methodologies. These methods, however, have yet to find a footing as a viable component of the conventional design processes due to lack of representative datasets and the inhibitive cost of generating real-world data sets. The struggle of conventional machine learning algorithms to generate or predict performance of out-of-sample designs also limits their utility for real-world design processes.

You will be joining a collaborative group dedicated to addressing complex real-world engineering problems. The group is focused on conceptualizing cutting-edge data-driven topology and optimization methodologies. These techniques are specifically developed with the aim of solving real-world engineering challenges such as fluid structures, turbomachinery, meta-materials, etc. The University of Southampton boasts extensive HPC and experimental facilities making this a unique opportunity to conduct high fidelity, multi-disciplinary research and collaborate with world-class researchers.

We are actively searching for a highly motivated candidate with the following qualifications:

1. Background in Mechanical engineering, mathematics, physics or computer sciences is highly desirable
2. Proficiency in at least one high level scientific computing language such as MATLAB, Python, etc
3. Enthusiasm for exploring topology optimization, surrogate modeling algorithms and interdisciplinary research
4. Demonstrated capability to research independently and collaboratively
5. Passion to explore new scientific idea, solving problems with scientific rigor and about and producing high-impact research

If you wish to discuss any details of the project informally, please contact Dr. Haris Moazam Sheikh, Email: h.m.sheikh@soton.ac.uk

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or >3.3/4.0 GPA) and preferably an MSc. in Mechanical Engineering, Applied Mathematics or other relevant subjects

Closing date: The position will remain open until filled.  Applications will be considered in the order that they are received, and 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:

Please apply directly online, by clicking the 'Apply' button, above. Select programme type (Research), 2024/25, Faculty of Physical Sciences and Engineering, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Haris Moazam Sheikh.

Applications should include:

• Curriculum Vitae
• Two reference letters
• Degree Transcripts/Certificates to date
• and a Cover letter in place of a Research Statement

For further information please contact: feps-pgr-apply@soton.ac.uk

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