Kingston University

Ref.: 534409 Work type: Full-time Department: School of Future Media (31200) Categories: Teaching Staff Applications are invited for appointment as Senior Lecturer/Lecturer/Assistant Lecturer (several posts) in the School of Future Media (Ref.: 534409), to commence on August 1, 2026 or from as soon as possible thereafter. The appointment rank will be determined according to qualifications and experience of the successful candidate. The initial appointment will be on a two-year fixed-term basis, with the possibility of renewal subject to satisfactory performance and funding availability. Applicants should possess a Master’s degree or equivalent in Media/Game Studies, Computer Sciences, Artificial Intelligence, Data Science or related fields of study, with a substantial track record of professional experience in the media industries. Proficient knowledge of digital media/AI applications/game studies is required. Experience in digital media projects with knowledge of Asia will be a definite advantage. Priority will be given to those with experience in designing and teaching professional courses at the tertiary level. Applicants with less experience may be considered for appointment as Lecturer or Assistant Lecturer. The appointees will be responsible for teaching and leading curriculum design at the undergraduate and postgraduate level in one of the following areas, as well as undertaking administrative duties at the Division level. Journalism: AI applications in journalism practices, entrepreneurship, business journalism; Documentary: video production, directing, post-production; AI Film: generative AI models, model training, AI video editing and post-production, 3D and animation integration, audience and workflow design; and Global Creative Industries: gaming and digital humanities, visual arts and museum studies, music and performing arts, visual communications.  A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. At current rates, salaries tax does not exceed 15% of gross income. The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 15% of basic salary for Senior Lecturer/Lecturer and 10% for Assistant Lecturer. Housing benefits will be provided for Senior Lecturer as applicable. The University only accepts online applications for the above posts. Applicants should upload an up-to-date CV and teaching statement. Review of applications will start as soon as possible and continue until June 30, 2026, or until the position is filled, whichever is earlier.

Position Overview: Mohammed VI Polytechnic University (UM6P) invites applications for a highly qualified Postdoctoral Researcher to join our research initiative focusing on the integration of Artificial Intelligence (AI) in Chemical Process Systems Engineering (CPSE). The position addresses key challenges in process intensification, sustainability, and advanced process control, aiming to develop AI-driven frameworks for multi-scale modeling, multi-objective optimization, and predictive control of complex chemical and biochemical processes. The research will contribute to next-generation smart manufacturing systems, aligned with Industry 4.0 paradigms, and target applications in sustainable energy production, green chemistry, circular economy, and carbon capture, utilization and storage (CCUS). Scientific Challenges Addressed in the Position: Non-linear and dynamic system modeling of chemical processes involving complex thermodynamics and transport phenomena. Optimization under uncertainty and robust decision-making for process design and operational strategies. Integration of first-principles (mechanistic) models with data-driven models (hybrid modeling) for improved accuracy and generalization. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process management. Addressing data sparsity and data quality issues in industrial process data streams for reliable AI model training. Design of digital twins for process monitoring, fault diagnosis, and predictive maintenance in chemical plants. Key Responsibilities: Create and implement hybrid AI models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks and grey-box modeling) to enable predictive simulations of chemical and biochemical processes. Construct multi-objective optimization frameworks (Pareto optimization) to evaluate trade-offs among economic, energy efficiency, and environmental performance metrics. Utilize reinforcement learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical processes for virtual commissioning and optimization. Examine extensive heterogeneous data sets (including historical process data, sensor data, and laboratory findings) using advanced AI approaches such as unsupervised learning, transfer learning, and anomaly detection. Collaborate with process engineers and experimentalists to validate models, demonstrate them at pilot scales, and transfer technology to industry partners. Share research results through peer-reviewed publications, conference talks, and patent filings when relevant. Oversee graduate students and support capacity building in AI for CPSE at UM6P. Required Qualifications: Ph.D. in Chemical Engineering, Process Systems Engineering, Artificial Intelligence, Data Science, or a related discipline. Proven experience in process modeling (steady-state and dynamic) using simulation software such as Aspen Plus, gPROMS, or COMSOL Multiphysics. Solid understanding of process control strategies, including model predictive control (MPC), nonlinear control, and optimal control theory. Proficiency in programming languages (Python, MATLAB) and experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience in data-driven modeling, deep learning, and reinforcement learning algorithms applied to chemical processes. Track record of scientific publications in peer-reviewed journals in AI, chemical engineering, or process systems engineering. Excellent communication skills and ability to collaborate in multidisciplinary and international teams. Application Process: Candidates are invited to submit the following documents (compiled in a single PDF): A cover letter outlining their research vision, motivation, and relevant experiences. A comprehensive Curriculum Vitae (CV) including a list of publications and any patents. Contact details of two academic referees. 

Lingnan University is one of the eight publicly funded institutions in the Hong Kong Special Administrative Region (HKSAR) of the People’s Republic of China (PRC) and has the longest established tradition among the local institutions of higher education. It is widely recognised for providing quality education with a focus on whole-person development and conducting high-impact research for a better world. Moving forward, Lingnan University is well positioned to take lead as a comprehensive university in arts and sciences in the digital era, with impactful research and innovations. Lingnan University offers undergraduate, taught postgraduate, and research postgraduate programmes in the Faculties of Arts, Business, Social Sciences, and the Schools of Data Science, Graduate Studies and Interdisciplinary Studies. To foster interdisciplinary collaboration and scientific progress, Lingnan University established the Lingnan University Institute for Advanced Study (LUIAS), attracting distinguished scholars from around the world to collaborate with its faculty and students. With traditional strengths in arts, business, social sciences, and interdisciplinary studies, the University aims to equip students with practical knowledge and critical thinking skills to thrive in the future. Subsequent to the establishment of the School of Data Science and LUIAS, Lingnan University is transforming into a hub for global leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/. Applications are now invited for the following posts: Research Assistant Professor (two posts) Department of Sociology and Social Policy (Post Ref.: 26/33) The Department of Sociology and Social Policy brings together scholars with international research experience and publication records in the major areas of Sociology and Social Policy. Over the years, our faculty members have been the recipients of the University’s Research Excellence Award and Teaching Excellence Award. The Department offers undergraduate teaching in Sociology, Social and Public Policy, and Health and Social Services Management, while hosting an MSocSc Programme in Comparative Social Policy (International) (IMCSP). We have been consistently successful in attracting MPhil and PhD students from around the world, particularly the recipients of the Hong Kong RGC Junior Research Fellow Scheme, and obtaining the General Research Fund (GRF) and other external competitive grants. For more information, applicants are advised to visit the departmental website. General Requirements Applicants should have obtained / been conferred a PhD degree in Sociology, Social Policy or any discipline related to computational social science, or an equivalent qualification for no more than five years prior to the commencement of the appointment, with relevant teaching and research experience. Applicants are required to provide their research portfolio, publication record, and teaching evaluation among other relevant information. Excellent communication and presentation skills in English are essential. Experience with conducting state-of-the-art social research will be a distinct advantage. The appointees should be able to take up teaching duties in some of the courses on the Bachelor of Social Sciences (Honours) Programme, including but not limited to: “Introduction to Sociology”, “The Making of Hong Kong”, “Social Innovation Seminar: Dialogue with Change-Makers”, “Non-Profit Organizations and the Voluntary Sector”, “Health and Social Service Project”, “Community-based Social Services” and “Social Innovation & Social Enterprises”. The appointees should be prepared to actively support the coordination and development of our teaching programmes, as well as the research endeavours of faculty members in the areas of Sociology and Social Policy. The appointees are expected to have a strong commitment to academic excellence and engagement in high-quality research and publication, and to submit applications for RGC grants, other local/overseas competitive grants and/or fellowship schemes. Appointment The conditions of appointment will be competitive. The remuneration will be commensurate with qualifications and experience. Fringe benefits include annual leave, medical and dental benefits, mandatory provident fund, gratuity, incoming passage and baggage allowance for the eligible appointees. The appointments will normally be made on a fixed-term contract of up to three years. Application Procedure (online application only) Please click "Apply Now" to submit your application. Applicants shall provide names and contact information of at least three referees to whom applicants’ consent has been given for their providing references. Personal data collected will be used for recruitment purposes only. We are an equal opportunities employer. The review of applications will start from late-February 2026 and will continue until the posts are filled. Qualified candidates are advised to submit their applications early for consideration. The University reserves the right not to make an appointment for the posts advertised, or to fill the posts by invitation or by search. We regret that only shortlisted candidates will be notified.