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Bo Chen

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1 week ago

Rapid Alloy Discovery and Characterisation of Additively Manufactured Type 316 Stainless Steel and Its Advanced Variants University of Southampton in United Kingdom

Degree Level

PhD

Field of study

Mechanical Engineering

Funding

Funded PhD Project (Students Worldwide)

Deadline

Mar 31, 2026

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Country

United Kingdom

University

University of Southampton

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Where to contact

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Keywords

Mechanical Engineering
Materials Science
Artificial Intelligence
Additive Manufacturing
Solid Mechanics
X-ray Diffraction
3d Printing
Automation
Transmission Electron Microscopy
Machine learning

About this position

This fully funded PhD project at the University of Southampton offers an exciting opportunity to accelerate the discovery and characterisation of additively manufactured Type 316 stainless steel and its advanced variants. Supervised by Professor Bo Chen and Dr Andrew Hamilton, the research aims to revolutionise bulk alloy discovery for additive manufacturing by integrating smart design, 3D printing of material libraries, and AI-assisted workflows. The project addresses a critical challenge in Materials 4.0: efficiently exploring new alloys tailored to the unique thermal history of additive manufacturing processes.

Through computational screening of candidate alloys and innovative 3D printing techniques, you will create compositional libraries and bespoke multi-sample fixtures to enable high-throughput characterisation and testing. Automated workflows will facilitate rapid data collection using X-ray diffraction and scanning electron microscopy, allowing for the extraction and testing of multiple samples simultaneously. The integration of AI companion agents across the pipeline will streamline materials selection, testing coordination, and data curation, driving a digital transformation in materials research.

As a PhD student, you will benefit from access to state-of-the-art research infrastructure, including the Additive Materials and Structures Research Laboratory, Testing and Structures Research Laboratory (TSRL), and Material Innovation Laboratory. Comprehensive training on experimental facilities will be provided, ensuring you develop expertise in advanced manufacturing and characterisation techniques.

Entry requirements include a first-class or upper second-class (2:1) honours degree (or international equivalent) in Mechanical Engineering, Materials Science, or a closely related discipline. A Master’s degree is desirable but not essential. Familiarity with additive manufacturing processes, experience with microstructural characterisation tools (SEM, XRD, EBSD), and interest in data-driven methods (machine learning, Python programming, data curation) are advantageous. Strong problem-solving skills, independence, teamwork, and motivation to contribute to digital transformation in materials research are essential.

The position is fully funded for both UK and international students, with bursaries and scholarships available. Funding is awarded on a rolling basis, so early application is encouraged. The University of Southampton is committed to equality, diversity, and inclusivity, offering flexible working patterns, generous maternity policy, onsite childcare, and a range of benefits to support well-being and work-life balance. Sustainability is a core value, as demonstrated by the Platinum EcoAward.

Applications are considered as received and the position will be filled once a suitable candidate is identified. The closing date is 31 March 2026. To apply, submit your application online, select the appropriate programme, and include a research proposal, CV, two reference letters, and degree transcripts/certificates. For further information, contact [email protected].

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants must hold a first-class or upper second-class (2:1) honours degree or international equivalent in Mechanical Engineering, Materials Science, or a closely related discipline. A Master’s degree in a relevant field is desirable but not essential. Familiarity with additive manufacturing processes or willingness to learn advanced manufacturing techniques is required. Experience with microstructural characterisation tools such as SEM, XRD, or EBSD is advantageous. Interest in or experience with data-driven methods, including machine learning, Python programming, or data curation, is preferred. Strong problem-solving skills and the ability to work independently and as part of a multidisciplinary team are expected. Motivation to contribute to the digital transformation of materials research is essential.

How to apply

Apply online via the University of Southampton postgraduate application portal. Select programme type 'Research', 2025/26, Faculty of Engineering and Physical Sciences, then choose 'PhD Eng & Env (Full time)'. In Section 2 of the application form, insert the name of the supervisor Prof Bo Chen. Applications should include a research proposal, CV, two reference letters, and degree transcripts/certificates. For further information, contact [email protected].

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