Responsible AI and Digital Twins for Sustainable Biodiversity Net Gain

About the Project

The increasing generation, adoption and deployment of Artificial Intelligence (AI) technologies that could impact humanity, heritage and environment raise continuously interests and also concerns from general public, regulatory bodies, governments, industries and scientists. Responsible and Sustainable AI solutions are currently driven by data-centric models and processes to study fundamental theories and mechanisms to create and apply AI models in real world applications.

This research theme of the interdisciplinary contributions to knowledge and real-world applications of Responsible and Sustainable AI models and Digital Twins resources for environmental resources particularly aligned with the current Biodiversity Net Gain (collected from our research or industry partners particularly in domains such as environment, social media, heritage, ecology) explore, propose, define, characterise, evaluate, test and validate agentic and generative AI algorithms, building on our renowned expertise in machine learning, federated learning, reinforcement learning, explainable AI, big data and AI model governance and their applications. The project also explores their validation through a number of case studies.

The primary objective of the project is to fill the knowledge gap about the relationship between point cloud segmentation, environment and BNG regulations and processes, and their use. The digital twin resources include 2D and 3D (satellite, drone, photogrammetry and mobile) images, 3D point clouds within the environment and cultural heritage domains with applications for data collected from the Bradford Metropolitan district, also international case studies and sites. The theme addresses current research to gain better understanding and use of 3D point clouds, multimodal cultural heritage, and Biodiversity Net Gains (of flora and fauna) including their core ideas and practical uses in maintenance, use, recreation, aligned also with UN SDGs. Biodiversity Net Gain (BNG) applications include video, image, audio and point cloud processing aligned with BNG real data. The project focuses on diverse applications for flora, fauna and environment information processing, including crowd, litter, cultural events and traffic related supervised and unsupervised real information processing. Biodiversity Net Gain project members work within a team from Department of Place of Bradford Metropolitan District City Council looking in analytics and review of biodiversity topics: https://www.bradford.ac.uk/news/archive/2022/bradfords-first-digital-twin-has-been-completed.php

What we offer:

As a successful candidate, you will be based in the School of Computer Science, AI & Electronics of the University of Bradford. The PhD students join our dynamic and motivated Artificial Intelligence Research (AIRE) Group comprising of PhD and taught students and interns, postdoctoral researchers, and research active academic staff. This research project includes collaboration with Visualising Heritage, School of Archaeological & Forensic Sciences, Bradford Metropolitan District City Council’s Department of Place, and BD25 - Bradford 2025 UK City of Culture.

The AIRE group and leader have a renowned and long-standing research knowledge and expertise in fundamental research, collaborative successful contributions to knowledge and applications, and international networking and exchanges. You could also benefit of successful Turing University Network membership environment, and opportunities abroad through Turing Scheme placements.

You will have the opportunity to present your work at relevant conferences and research events; publish contributions in scientific journals; participate in academic and industry activities, and build your research expertise with a highly knowledgeable and friendly academic inter-disciplinary research team. The University of Bradford is offering a comprehensive and highly supportive doctoral training environment. The University of Bradford is a major BD25 partner of Bradford 2025 UK City of Culture.

Eligibility/ Candidate Profile:

Candidates are expected to hold (or be about to obtain) a minimum 2:1 Hons degree (or equivalent) in a related area / subject, e.g. Computer Science, Data Science, Informatics/Information Science, Big Data, AI, IoT, Mathematics, Statistics, Physics, Philosophy. MSc, MEng, MA or relevant experience in a related discipline is highly desirable. Other academic and career background will be analysed based on specific expertise relevant to this research theme.

How to apply

Formal applications can be submitted via the University of Bradford web site. Applicants should register an account, select 'Postgraduate Research' as the course type and use the keywords 'computer science'. Please include the project title on the Research Proposal section; applicants are not required to supply a research proposal for this project.

Informal enquiries are also welcome.

Funding Notes

This is a self-funded PhD project; applicants will be expected to pay their own fees or have a suitable source of third-party funding. UK students may be able to apply for a Doctoral Loan from Student Finance for financial support.