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Faculty Position in AI for Theoretical and Physics-Informed Modelling

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Xi'an Jiaotong-Liverpool University

Wuzhong District, Suzhou, China, 215000

Academic Connect
5 Star Employer Ranking

Faculty Position in AI for Theoretical and Physics-Informed Modelling

Position overview

Contract type: Fixed-term, renewable. 3rd contract is open-ended

About the Department of Physics

The Department of Physics is part of the School of Mathematics and Physics (SMP) at Xi’an Jiaotong-Liverpool University (XJTLU). Research in the Department seeks to explore and explain fundamental aspects of the world we live in, from the smallest subatomic particles to the Universe as a whole. Building on its existing strengths, the Department is expanding into application-oriented areas that can drive technological innovation and help address major global challenges. These include AI for Science, quantum technologies, advanced imaging, and materials-related research.

Position introduction

The Department of Physics at Xi’an Jiaotong-Liverpool University (XJTLU) invites applications for a faculty position in AI for Theoretical and Physics-Informed Modelling. We seek a highly motivated and well-qualified candidate with a strong background in theoretical and computational physics, with expertise in physics-based modelling, numerical simulation, and AI-enhanced scientific computing.

Responsibilities

  • Conduct high-quality research and publish in top journals;
  • Actively apply for national and international research funding;
  • Supervise research projects of undergraduate and PhD students;
  • Deliver undergraduate and graduate courses in physics and mathematics in English;
  • Actively participate in departmental and university affairs, and promote interdisciplinary collaboration, particularly with data science and artificial intelligence.

Essential Qualifications/Experience

  • A PhD in Physics, Astronomy, or a closely related discipline;
  • Postdoctoral research experience or equivalent academic experience;
  • Demonstrated ability or strong potential in undergraduate and postgraduate teaching;
  • Solid background in observational, experimental, or data-intensive astrophysics;
  • Fluency in written and spoken English.
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