Postdoctoral Research Fellow (Principal Investigator: Prof Alain Chong and Prof Ying Weng)

University of Nottingham Ningbo China

Prof. Alain Chong and Prof. Ying Weng are seeking an outstanding Postdoctoral Research Fellow to join the newly established Postdoctoral Research Station in Business Administration at the University of Nottingham Ningbo China, contributing to the development of the university’s research agenda.

Your Responsibility

Your key responsibilities include:

• Design and Develop Research: Formulate clear research objectives and contribute to the development of proposals for individual and collaborative projects, applying established and emerging methodologies to advance the research agenda.
• Conduct and Analyze Research: Collect, manage, and rigorously analyze complex datasets; interpret results; critically evaluate existing literature; and generate original insights that align with project goals.
• Disseminate Findings: Prepare high-quality manuscripts for submission to leading journals, present research at national and international conferences, and contribute to the visibility and impact of the research team.
• Secure Funding: Identify opportunities and contribute to the preparation of competitive grant applications to national and international funding bodies.
• Build Networks and Collaborations: Engage with internal colleagues and external partners (academic and industry) to exchange ideas, explore opportunities for collaboration, and establish partnerships that strengthen research outcomes.

About You

• Qualifications: PhD awarded within 3 years in business administration, computer science, information systems, data science, or a related discipline.
• Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage.
• Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning architectures (CNNs, RNNs). Experience with explainable AI (e.g., SHAP, LIME) is preferred.
• Quantitative Analysis: Demonstrated ability to handle multimodal datasets, conduct statistical analysis, and apply predictive modeling and validation techniques.
• Research & Publication: Skilled at critically reviewing literature, designing rigorous studies, and producing publications for high-impact journals.
• Collaboration & Communication: Excellent oral and written English communication skills, with the ability to present technical findings clearly. Knowledge of Chinese is a plus. Ability to work both independently and within multidisciplinary teams.
• Practical Experience: Prior hands-on research in AI applications / digital innovations in water ecological environment will be an asset.

About Us

Join a unique British University in China. University of Nottingham Ningbo China (UNNC) was the first Sino-foreign university to open its doors in China. Located in Ningbo, this award winning campus offering a UK-style education has grown to establish a student body of over 10,000 in just 22 years.

About Postdoctoral research station in Business Administration. Postdoctoral research station in Business Administration was approved to establish in Nov 2023. It is UNNC’s first postdoctoral research station, and its founding deeply aligns with the national strategic needs in promoting talent cultivation and innovation as well as that of UNNC. UNNC’s undergraduate programme of Business Administration was launched in 2004 and the doctoral programme in 2009. The subject has been listed among the world’s top academic subjects by Shanghai Ranking for four consecutive years. The discipline of Business Administration has also established teaching and research platforms at multiple levels and carried out in-depth industry university research cooperation with world renowned enterprises such as Microsoft and Amazon. In the future, UNNC will incorporate the development of the postdoctoral research station into the agenda of the university to provide talent support in efforts to promote scientific and technological innovation as well as economic and social development.

About the Research Team. Prof. Alain Chong is Vice Provost for Global Engagement and Partnerships and Chair Professor of Information Systems at the University of Nottingham Ningbo China. His research explores digital innovation, disruptive technologies, and their impact on business and society. He serves as Co-Editor-in-Chief of Industrial Management & Data Systems and as Associate Editor for Information & Management and Decision Support Systems. For details, please refer to the link: https://research.nottingham.edu.cn/en/persons/alain-chong; 

Prof. Ying Weng is Course Director for Computer Science with Artificial Intelligence, Professor in Computer Science. She obtained PhD in Signal & Information Processing at Chinese Academy of Sciences, and Postdoctor at Imperial College London. She received the Newton Research Collaboration Award by UK Royal Academy of Engineering, Best Paper Award at International Conference on Automation & Computing, and 1st Place Prize in the international ASNR-MICCAI BraTS Challenges. She is with membership of Editorial Board for Expert Systems with Applications, Elsevier. For details, please refer to the link: https://research.nottingham.edu.cn/en/persons/ying-weng.  

About the Project. This project focuses on research in Explainable Artificial Intelligence and Causal Machine Learning, applied to the intelligent monitoring and early warning of key water ecological environment indices, including prediction and management tasks. A network of reservoirs forms the backbone of the region’s water resource infrastructure, playing an essential role in ensuring urban water supply, mitigating flood risks, and supporting agricultural irrigation. However, the intricate interactions between natural hydrological cycles — such as precipitation and evaporation — and human operational controls, including release scheduling and storage regulation, introduce substantial complexity. This dynamic interplay makes the multi-reservoir system both ideal and challenging for developing advanced spatiotemporal forecasting models. By integrating causal inference with interpretable AI techniques, the project aims not only to improve prediction accuracy but also to uncover underlying cause-effect relationships, thereby enabling transparent, reliable early warnings for sustainable water resources development.

Candidates are expected to submit a research proposal that builds on this project summary.

Your Remuneration, Benefits and Support

You will be offered a fixed term contract with University of Nottingham Ningbo China for 2 years. You will be offered a minimum annual salary package of RMB269,906 with competitive benefits package. Postdoctoral Research Fellow is also able to apply RMB50,000 research funding after they start their research.

How to Apply

Applicants should submit an application via our on-line application system (by clicking on the 'Apply' button above) before May 20, 2026. Only on-line applications will be accepted. Referees will be contacted prior to interview and interviews will take place in Ningbo China.

Applications should include but are not limited to the following:

• A cover letter
• An up-to-update CV includes academic and research achievement list
• A Research proposal (Please refer to the attached project summary)

Enquiries

Informal enquiries regarding the research project may be addressed to Ying Weng Ying.Weng@nottingham.edu.cn or Alain Chong Alain.Chong@nottingham.edu.cn. If you are unable to apply on-line please contact the Human Resources Office, Tel: 86 574 88180000(Ext. 8854).

Equality and Diversity

University of Nottingham Ningbo China is an equal opportunity employer. We are committed to providing a fair, equitable, and mutually supportive learning and working environment for our students and staff. It is our intention to ensure that job applicants and staff are treated solely on the basis of their merits, abilities, and potential, regardless of gender, race, colour, nationality, ethnic or national origin, age, socio-economic background, disability, religious or political beliefs, trade union membership, family circumstances, sexual orientation, or other irrelevant distinction.