Faculty Position in AI for Theoretical and Physics-Informed Modelling [Open Rank]

Position Overview

School: School of Mathematics and Physics
Department: Department of Physics
Position: Faculty Position in AI for Theoretical and Physics-Informed Modelling [Open Rank]
Location: Suzhou, China
Job ID: 4367
Contract Type: Fixed-term, renewable. 3rd contract is open-ended

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. Research interests may include (but are not limited to) interstellar medium and astrochemical modelling, multiphysics systems, complex physical processes, and data-driven scientific simulation. The successful candidate is expected to play a key role in developing physics-informed artificial intelligence methods that integrate physical laws, numerical solvers, and machine learning, with strong emphasis on interpretability, reliability, and scientific validity. The position will contribute substantially to both high-quality teaching and the long-term development of AI-for-Science education and research at XJTLU.

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

All applicants must have:

• 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.