AI-Driven Atomic-Scale Materials Research Fellow

University of Sydney; Australia; On-site; AUD 118,000 - 126,000; Full time

Job summary

The University of Sydney’s School of Aerospace Mechanical and Mechatronic Engineering is seeking a Postdoctoral Research Associate in AI Enabled Atomic-Scale Materials Characterisation. The role spans advanced microscopy, atom probe tomography (APT) and AI-driven data analysis in a collaborative, cross-disciplinary research setting.

You will conduct cutting-edge studies, supervise HDR students, and contribute to grant development while publishing in leading journals and presenting at

Qualifications

• PhD in Materials Science and Engineering or related field.
• Expertise in advanced microscopy and microanalysis, especially APT.
• Experience with TEM/SEM/EBSD/XRD and large datasets.
• Strong programming and AI/data-driven materials research experience desirable.

Responsibilities

• Conduct innovative research using advanced microscopy and characterisation techniques to investigate atomic-scale structure, chemistry and materials behaviour.
• Develop AI-enabled approaches to materials characterisation, data analysis and scientific discovery.
• Collaborate with multidisciplinary research teams, industry partners and international collaborators to deliver high-impact research outcomes.
• Contribute to student supervision, research training, grant development and dissemination of research through leading journals and conferences.

Skills

AI / ML experience

Programming

Quantitative analysis

Multidisciplinary collaboration

Education

PhD in Materials Science and Engineering, Physics, Materials Characterisation, Computational Materials Science, or related

Tools

Atom Probe Tomography (APT)

TEM

SEM

EBSD

XRD

Job description

The University of Sydney’s School of Aerospace Mechanical and Mechatronic Engineering is seeking a Postdoctoral Research Associate in AI Enabled Atomic-Scale Materials Characterisation. The role spans advanced microscopy, atom probe tomography (APT) and AI-driven data analysis in a collaborative, cross-disciplinary research setting.

You will conduct cutting-edge studies, supervise HDR students, and contribute to grant development while publishing in leading journals and presenting at