PhD Studentship in AI-Augmented Group Model Building

RFCSR; Glasgow; On-site; GBP 18,000 - 21,000; Full time

Job summary

The University of Strathclyde, Strathclyde Business School in Glasgow, invites applications for a PhD studentship in AI-Augmented Group Model Building. This research explores integrating AI with participatory modelling to enhance collaborative decision-making in organisation and public policy contexts.

You will work under experienced supervisors, develop AI tools for group model building, and contribute to high-impact publications.

Qualifications

• First-class or upper second-class honours degree (or international equivalent) in a relevant discipline such as management science, computer science, artificial intelligence, operations research, or a related field
• A master’s degree in a relevant subject is desirable
• Applicants must meet the English language requirements where applicable
• Demonstrated interest in interdisciplinary research combining AI and decision sciences
• Strong analytical and problem-solving skills
• Ability to undertake independent and collaborative research
• Programming or computational modelling experience is advantageous
• Effective written and verbal communication skills
• Ability to engage with interdisciplinary research environments

Skills

Analytical skills

Problem-solving

Programming

Communication

Interdisciplinary research

Education

Honours degree in relevant discipline

Master's degree desirable

Tools

Computational modelling

Job description

PhD Studentship in AI-Augmented Group Model Building

University of Strathclyde – Department of Management Science, Strathclyde Business School
Glasgow, United Kingdom

General Description
The University of Strathclyde is offering a PhD studentship in AI-Augmented Group Model Building within the Department of Management Science at Strathclyde Business School. This research opportunity focuses on advancing the integration of artificial intelligence techniques with group model building approaches, with the aim of enhancing collaborative decision-making and complex problem-solving processes.

The project will explore how AI can support and augment participatory modelling methods, particularly in contexts where stakeholders engage in system dynamics modelling to address complex organisational or societal challenges. The successful candidate will investigate the design, development, and application of AI tools to facilitate group model building, improving efficiency, inclusivity, and analytical depth.

The research will involve interdisciplinary approaches, combining management science, artificial intelligence, systems thinking, and decision sciences. The candidate will work closely with experienced academic supervisors and may engage with external partners where relevant. The programme provides access to advanced research training, academic mentorship, and opportunities to contribute to high-impact publications and conferences.

Strathclyde Business School is internationally recognised for its research excellence and strong links with industry and public sector organisations. The University offers a supportive and collaborative research environment, along with professional development opportunities to prepare graduates for careers in academia, industry, and policy.

Eligibility Criteria

A first-class or upper second-class honours degree (or international equivalent) in a relevant discipline such as management science, computer science, artificial intelligence, operations research, or a related field

A master’s degree in a relevant subject is desirable

Applicants must meet the University of Strathclyde’s English language requirements where applicable

Demonstrated interest in interdisciplinary research combining AI and decision sciences

Required Expertise/Skills

Strong analytical and problem-solving skills

Ability to undertake independent and collaborative research

Programming or computational modelling experience is advantageous

Effective written and verbal communication skills

Ability to engage with interdisciplinary research environments

Salary Details
Not specified (funding or studentship support may be available depending on eligibility and funding arrangements)