Fully Funded PhD Studentship in Multimodal AI for Early Detection of Neurodevelopmental Disorders
University of Bedfordshire
Package: Three-year studentship Job category/type: Research Fully Funded PhD Studentship in AI for Early Detection of Neurodevelopmental Disorders (UK Home Applicants Only) Project: Multimodal AI for Early Detection of Neurodevelopmental Disorders Falcon Foundation Doctoral Programme in Collaboration with The University of Bedfordshire and Luton AI A full-time, fully funded PhD studentship for UK Home students is available at the University of Bedfordshire to develop cutting-edge multimodal AI technologies that...
Package: Three-year studentship Job category/type: Research Fully Funded PhD Studentship in AI for Early Detection of Neurodevelopmental Disorders (UK Home Applicants Only) Project: Multimodal AI for Early Detection of Neurodevelopmental Disorders Falcon Foundation Doctoral Programme in Collaboration with The University of Bedfordshire and Luton AI A full-time, fully funded PhD studentship for UK Home students is available at the University of Bedfordshire to develop cutting-edge multimodal AI technologies that...
Opportunity details
Package: Three-year studentship Job category/type: Research Fully Funded PhD Studentship in AI for Early Detection of Neurodevelopmental Disorders (UK Home Applicants Only) Project: Multimodal AI for Early Detection of Neurodevelopmental Disorders Falcon Foundation Doctoral Programme in Collaboration with The University of Bedfordshire and Luton AI A full-time, fully funded PhD studentship for UK Home students is available at the University of Bedfordshire to develop cutting-edge multimodal AI technologies that could transform the early detection of neurodevelopmental disorders and improve outcomes for children and families. The studentship forms part of the Falcon Foundation Doctoral Programme, an initiative designed to widen access to doctoral study for talented individuals. The successful candidate will also become part of Luton AI, the University of Bedfordshire’s applied AI ecosystem. Luton AI brings together academic research, specialist facilities, external partners and real-world projects to support the responsible development and practical application of artificial intelligence. Through the Falcon Foundation Doctoral Programme, the studentship provides an annual stipend, full tuition fees, academic supervision, access to research infrastructure and specialist facilities, doctoral training, and wider researcher development support. Falcon Foundation is a UK Charity no 1210094 registered with the Fundraising Regulator. Funding The studentship will provide: Full Home University tuition fees for three years – please note, this opportunity is only available to UK Home students. An annual stipend for up to three years. Access to specialist research facilities, computing infrastructure and doctoral training. Academic supervision and support from the University’s re...
Eligibility
Package: Three-year studentship Job category/type: Research Fully Funded PhD Studentship in AI for Early Detection of Neurodevelopmental Disorders (UK Home Applicants Only) Project: Multimodal AI for Early Detection of Neurodevelopmental Disorders Falcon Foundation Doctoral Programme in Collaboration with The University of Bedfordshire and Luton AI A full-time, fully funded PhD studentship for UK Home students is available at the University of Bedfordshire to develop cutting-edge multimodal AI technologies that could transform the early detection of neurodevelopmental disorders and improve outcomes for children and families. The successful candidate will also become part of Luton AI, the University of Bedfordshire’s applied AI ecosystem. The successful candidate will work closely with academic and clinical collaborators to support the collection, management and analysis of multimodal research data. Research environment The successful candidate will undertake the project within the University of Bedfordshire’s growing artificial intelligence research and innovation environment and will be connected to the work of Luton AI.
Requirements
Applicants should normally have: A good honours degree, normally at least a UK 2:1 or international equivalent, in computer science, artificial intelligence, data science, biomedical engineering, electronic engineering or a closely related subject. A relevant master’s degree, or equivalent research or professional experience, would be advantageous. Applicants with relevant professional or technical experience who can demonstrate their ability to undertake doctoral-level research may also be considered. Knowledge Applicants should demonstrate knowledge of one or more of the following areas: Artificial intelligence and machine learning. Computer vision and video analysis. Deep learning. Multimodal data analysis. Signal processing or sensor-data analysis. Explainable or responsible AI. Healthcare, biomedical or clinical data applications. Knowledge of neurodevelopment, infant movement analysis or healthcare research would be beneficial but is not essential. Experience Experience in one or more of the following would be advantageous: Programming in Python or a comparable language. Using machine-learning frameworks such as PyTorch or TensorFlow. Working with image, video, time-series or sensor data. Designing and evaluating machine-learning models. Conducting quantitative research or statistical analysis. Working in multidisciplinary research environments. Preparing academic reports, technical documentation or research publications. Skills and competencies The successful candidate will be expected to demonstrate: A logical, analytical and methodical approach to problem-solving. The ability to plan and undertake research independently. Strong written and verbal communication skills. The ability to explain complex technical ideas clearly to specialist and non-specialist aud...
Funding and benefits
Funding eligibility: UK Students. Funding amount: Please see below. The studentship will provide:
Required documents
curriculum vitae, reference, personal statement
How to apply
Applicants should submit: A completed University PhD application through the University’s Job portal A current curriculum vitae, including full details of all relevant degrees and qualifications. A personal statement explaining their interest in the project, relevant skills and experience, and suitability for doctoral study. A short, fully referenced survey of the relevant research field, approximately 750-1,500 (not including references) words in length. This should provide the academic background to the project, summarise current approaches to infant movement analysis and the early detection of neurodevelopmental disorders, and review relevant developments in computer vision, multimodal sensing, machine learning and explainable AI. The statement should identify key limitations or gaps in the existing literature and briefly explain how the proposed PhD research could address them. Applicants should use appropriate peer-reviewed academic sources and provide a complete reference list. Contact details for two academic or professional referees. Please note that you may upload a maximum of two files. Each file must be no larger than 2 MB and must be in DOC, DOCX, PDF, RTF or TXT format. Applications must be submitted by Sunday 16th August 2026. The University of Bedfordshire, Luton AI and the Falcon Foundation are committed to widening participation in doctoral education and creating opportunities for talented researchers from a broad range of backgrounds.
Open the official application information
Verify the deadline and final conditions on the official provider page before submitting an application.
Benefits
Funding eligibility: UK Students. Funding amount: Please see below. The studentship will provide:
Eligibility summary
Package: Three-year studentship Job category/type: Research Fully Funded PhD Studentship in AI for Early Detection of Neurodevelopmental Disorders (UK Home Applicants Only) Project: Multimodal AI for Early Detection of Neurodevelopmental Disorders Falcon Foundation Doctoral Programme in Collaboration with The University of Bedfordshire and Luton AI A full-time, fully funded PhD studentship for UK Home students is available at the University of Bedfordshire to develop cutting-edge multimodal AI technologies that could transform the early detection of neurodevelopmental disorders and improve outcomes for children and families. The successful candidate will also become part of Luton AI, the University of Bedfordshire’s applied AI ecosystem. The successful candidate will work closely with academic and clinical collaborators to support the collection, management and analysis of multimodal research data. Research environment The successful candidate will undertake the project within the University of Bedfordshire’s growing artificial intelligence research and innovation environment and will be connected to the work of Luton AI.
Requirements
Applicants should normally have: A good honours degree, normally at least a UK 2:1 or international equivalent, in computer science, artificial intelligence, data science, biomedical engineering, electronic engineering or a closely related subject. A relevant master’s degree, or equivalent research or professional experience, would be advantageous. Applicants with relevant professional or technical experience who can demonstrate their ability to undertake doctoral-level research may also be considered. Knowledge Applicants should demonstrate knowledge of one or more of the following areas: Artificial intelligence and machine learning. Computer vision and video analysis. Deep learning. Multimodal data analysis. Signal processing or sensor-data analysis. Explainable or responsible AI. Healthcare, biomedical or clinical data applications. Knowledge of neurodevelopment, infant movement analysis or healthcare research would be beneficial but is not essential. Experience Experience in one or more of the following would be advantageous: Programming in Python or a comparable language. Using machine-learning frameworks such as PyTorch or TensorFlow. Working with image, video, time-series or sensor data. Designing and evaluating machine-learning models. Conducting quantitative research or statistical analysis. Working in multidisciplinary research environments. Preparing academic reports, technical documentation or research publications. Skills and competencies The successful candidate will be expected to demonstrate: A logical, analytical and methodical approach to problem-solving. The ability to plan and undertake research independently. Strong written and verbal communication skills. The ability to explain complex technical ideas clearly to specialist and non-specialist audiences. Careful research-data management and record-keeping. The ability to work effectively with academic, technical and clinical collaborators. An understanding of the ethical and responsible use of AI, particularly in healthcare. High levels of motivation, initiative and intellectual curiosity. The ability to manage competing priorities and work to agreed deadlines. A willingness to learn new technical and research methods. A willingness to engage proactively and professionally with the Falcon Foundation throughout the studentship.
Documents required
curriculum vitae, reference, personal statement
Language/test requirements
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