Phd-Software engineering for human-centric AI-driven smart system
PhD @Cranfield University posted 3 days agoJob Description
This research project focuses on developing a human-centric AI-driven smart sanitation platform for community toilet systems as part of the Gates Foundation’s global health initiative. Students will conduct interdisciplinary research combining software engineering, artificial intelligence, IoT development, and human-computer interaction to create intelligent software systems that serve both technical operators and end-users of smart toilet technologies.
The research involves developing IoT software for remote monitoring systems, designing user-centric applications for different stakeholder groups (technical personnel and toilet users), implementing AI-driven data analytics for system optimization, and creating predictive models for environmental and social impact assessment. Students will work with real-world deployment scenarios and collaborate with global organizations to ensure practical implementation and scalability.
Key Research Areas: Software engineering, AI/machine learning, IoT development, human-computer interaction, data analytics, user experience design, remote monitoring systems, energy optimization algorithms, and environmental impact modeling.
Human-centric AI-driven sanitation systems represent the future of smart infrastructure, particularly in global sanitation applications where technology must serve diverse user groups with varying technical expertise. With the increasing deployment of IoT-enabled sanitation systems worldwide, there is a critical need for intelligent software platforms that can bridge the gap between complex technical systems and end-users while providing actionable insights through AI-powered data analysis. This multidisciplinary field combines software engineering, artificial intelligence, and human-computer interaction to create solutions that are both technically sophisticated and genuinely user-friendly.
This project aims to develop a comprehensive AI-driven software platform for smart sanitation systems that serves multiple user groups through tailored interfaces and intelligent data processing. The research focuses on creating IoT software for remote monitoring, designing differentiated user experiences for technical operators versus end-users, implementing machine learning algorithms for system optimization and predictive maintenance, and developing AI models to simulate environmental and social impacts of large-scale deployment (100+ toilet systems). The platform will optimize energy consumption, enhance user experience, and provide valuable insights for system management and policy decisions.
Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships is creating leaders in technology and management globally. We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity Working Families. Cranfield University’s expertise in automation, embedded systems, and global development engineering provides an ideal research environment for this innovative project. The Gates Foundation, a leading global philanthropic organization committed to improving health and reducing inequality worldwide.
The research is expected to produce a deployable AI-driven sanitation system that significantly improves the usability, efficiency, and impact of smart sanitation systems. Results will include published research in top-tier journal, validated user interface designs, and AI models capable of predicting system performance and environmental impact. The platform aims to establish new standards for human-centric IoT software in development contexts and create scalable solutions that can support large-scale toilet deployment programs worldwide.
This project offers exceptional opportunities including collaboration with real users, access to large-scale IoT deployment data, specialized training in human-computer interaction and AI model development, and direct engagement with communities using the technology. Students will gain exposure to both cutting-edge research and real-world software deployment challenges, providing a unique combination of technical innovation and social impact that is highly valued in today’s technology industry.
Students will develop highly sought-after skills in AI, full-stack software development, IoT systems, user experience design, and data analytics. Graduates will possess strong technical capabilities in AI and software engineering, human-centered design thinking, international project experience, and a proven track record of developing AI solutions for real-world challenges, making them exceptionally competitive in today’s software development job market.
At a glance
- Application deadline06 Aug 2025
- Award type(s)MSc by Research, PhD
- Start date29 Sep 2025
- Duration of award1 year – MSc by Research. 3 years – PhD
- EligibilityUK, Rest of world
- Reference numberSWEE0299 – MSc by Research. SWEE3000 – Phd
Entry requirements
Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit graduates with backgrounds in:
- Software Engineering or Computer Science with experience in AI/ML, web development, or mobile applications
- Artificial Intelligence or Machine Learning with software development and deployment experience
- Human-Computer Interaction or User Experience Design with technical programming skills
- Data Science or Computer Engineering with interest in IoT and real-world applications
- Information Systems with experience in database design, API development, and system integration
Ideal candidates will have:
- Practical experience with machine learning model development and deployment
- Knowledge of IoT platforms, cloud services, and distributed systems
- Understanding of user-centered design principles and usability testing methods
- Experience with data visualization tools and dashboard development
- Interest in technology for social good and international development applications
This project is particularly suitable for students who:
- Are passionate about using AI and software engineering for global health impact
- Enjoy designing user-friendly technology for diverse populations
- Want to gain experience with large-scale IoT deployments and data analytics
- Are interested in the intersection of technology, human behavior, and social impact
- Seek to develop skills that bridge technical innovation with real-world problem solving.
Funding
Sponsored by Gates Foundation and Cranfield University, this studentship will provide a bursary of up to £1,350 per month (tax free) plus fees*. The funding will cover 12 months for MSc by Research students or 3 years for PhD students.
*This opportunity is open to Home and Overseas fee status students. Eligibility for Home fee status is determined with reference to UK Department for Education rules. As a guiding principle UK or Irish nationals who are ordinarily resident in either the UK or Republic of Ireland pay Home tuition fees. All other students (including those from the Channel Islands and Isle of Man) pay Overseas fees. Further advice can be found on the UK Council for International Student Affairs (UKCISA) website.
Cranfield Doctoral Network
Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.
How to apply
For further information please contact:
Name: Dr Yirui Jiang
Email: Yirui.Jiang@cranfield.ac.uk
If you are eligible to apply for this research studentship, please complete the online application form.
MSc by Research application form Ref: SWEE0299
PhD application form Ref: SWEE3000
Please note we will be interviewing as applications are received. This vacancy may be filled before the closing date so early application is strongly encouraged as soon as possible especially if you are an international student and may need additional documentation (visas etc)
For further information about application please visit Applying for a research degree.
