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Stella Pachidi

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PhD Studentships in Management Research (Technology, Work, Data, AI) at King's College London King's College London in United Kingdom

I am recruiting PhD students interested in technology, work, data, and AI at King's College London.

King's College London

United Kingdom

email-of-the@publisher.com

Dec 1, 2025

Keywords

Information Technology
Artificial Intelligence
Marketing
Business
Management
Qualitative Method
Human Resources
Strategy
Knowledge Collaboration
Research Management

Description

King's Business School at King's College London is inviting applications for its PhD programme in Management Research, with a particular interest in candidates who wish to study the intersection of technology and work. The programme welcomes applicants interested in topics such as data, artificial intelligence (AI) at work, the impact of AI on knowledge work and expertise, and knowledge collaboration. Students with a passion for using qualitative research methods to explore these areas are especially encouraged to apply and may be supervised by Dr. Stella Pachidi, Senior Lecturer in Technology and Work. The PhD in Management Research offers both full-time and part-time study options, starting in October 2026. The School is internationally recognized for its research excellence in management, business, human resource management, marketing, public services management, strategy, international management, and entrepreneurship. Students will benefit from a vibrant research environment, access to interdisciplinary training through the London Interdisciplinary Social Science Doctoral Training Partnership (LISS-DTP), and a supportive academic community. Applicants should have a strong academic background, typically with a relevant master's degree, and demonstrate a keen interest in management research related to technology, data, and AI. The programme is open to both UK and international students. Entry requirements include academic transcripts, references, a research proposal, and proof of English language proficiency for non-native speakers. Tuition fees for 2026/27 are £7,100 per year for UK students and £27,300 per year for international students (full-time). Part-time fees are £3,550 (UK) and £13,650 (international). Funding opportunities may be available through LISS-DTP and other sources, but are not guaranteed for all applicants. All doctoral students are supported by two academic supervisors and have access to dedicated workspaces, computing facilities, and financial support for conferences and specialized training. The application process consists of two rounds: the first deadline is 1st December 2025, and the second is 1st June 2026. Applications received after the first deadline will be considered for the second round. Prospective students are encouraged to contact Dr. Stella Pachidi directly if their research interests align with technology and work. For more information and to apply, visit the King's College London website.

Funding

Tuition fees for 2026/27 are £7,100 per year for UK students and £27,300 per year for international students (full-time). Part-time fees are £3,550 (UK) and £13,650 (international). Some funding opportunities may be available through the London Interdisciplinary Social Science Doctoral Training Partnership (LISS-DTP) and other sources, but funding is not guaranteed for all applicants.

How to apply

Submit your application online via the King's College London portal for the Management Research MPhil/PhD programme. Prepare your academic transcripts, references, research proposal, and English language test results if required. Contact Stella Pachidi directly if your research interests align with technology and work. Applications received after 1st December 2025 will be considered for the second round.

Requirements

Applicants should have a strong academic background, typically with a relevant master's degree in management, business, or a related field. International and home students are eligible. Interest in technology and work, qualitative research methods, and topics such as data, AI, knowledge work, or knowledge collaboration is encouraged. Specific entry requirements may include academic transcripts, references, a research proposal, and proof of English language proficiency for non-native speakers.

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