Michal Mackiewicz

[Fully-funded ARIES studentship covering fees, maintenance stipend (£20,780 p.a. for 2025/26), and a research training and support grant (RTSG). International applicants may have the difference between 'home' and 'international' fees waived. Does not cover relocation, visa, or health surcharge costs.] This fully-funded PhD studentship at the University of East Anglia offers an exciting opportunity to advance automation in aerial imaging for marine litter detection, in collaboration with Cefas. Marine litter poses a significant threat to ocean health and livelihoods, necessitating scalable, automated methods for data collection and analysis. The project aims to develop robust deep learning algorithms for classifying marine litter using both visible light and multispectral imaging data. The successful candidate will join the Colour & Imaging Lab within the School of Computing Sciences, benefiting from expertise in imaging solutions and close collaboration with scientists and engineers at Cefas. The research will involve extending an existing visible light dataset by collecting new multispectral data, training and evaluating deep learning models, and ensuring robustness to varying sensor configurations and illumination conditions. The project will also explore device-independent representations and domain adaptation techniques to future-proof the developed algorithms for use with emerging imaging technologies. Training will include imaging principles, laboratory measurement, computer vision, ArcGIS, and UAV operation, with potential for fieldwork. The studentship is ideal for candidates with a background or strong interest in environmental monitoring, artificial intelligence, computer vision, or multispectral imaging. Applicants should hold at least a UK 2:1 Honours degree (or equivalent) in Computer Science, Physics, Mathematics, or a related numerate discipline. English language proficiency (IELTS 6.5 overall, 6.0 in each category) is required. The ARIES studentship provides full funding, including tuition fees, a maintenance stipend (£20,780 p.a. for 2025/26), and a research training and support grant. International applicants may have the difference between 'home' and 'international' fees waived, though relocation, visa, and health surcharge costs are not covered. The project is scheduled to start on 1 October 2026, with an application deadline of 7 January 2025. For more information and to apply, visit the University of East Anglia's postgraduate research application portal. This is a unique opportunity to contribute to cutting-edge research at the intersection of environmental science, computer vision, and imaging technology.

[Fully-funded studentship covering fees, maintenance stipend (£20,780 p.a. for 2025/26), and research training and support grant (RTSG). International applicants may have the difference between 'home' and 'international' fees waived, but relocation and visa costs are not covered.] This PhD studentship at the University of East Anglia, in partnership with Cefas, focuses on advancing automation in aerial imaging for marine litter detection. Marine litter poses a significant threat to ocean health and livelihoods, necessitating scalable, automated methods for data collection and analysis. Cefas has developed a visible light deep learning algorithm and amassed a large training dataset covering 89 litter categories. However, to improve the accuracy of material type identification, the project will incorporate multispectral imagery and develop a new laboratory for characterising multispectral reflectance of materials. The successful candidate will use the existing visible light database and collect new multispectral data with the enhanced lab setup, aiming to train robust deep learning algorithms. These algorithms must be resilient to real-world illumination changes and adaptable to future imaging devices with unknown spectral sensitivities. The research will involve developing a multispectral imaging dataset of marine litter materials, designing and evaluating deep learning models for classification, implementing device-independent representations, and applying domain adaptation and transfer learning techniques to generalise models across different devices. The student will be based in the Colour & Imaging Lab at the School of Computing Sciences, benefiting from expertise in imaging solutions and opportunities to collaborate with scientists and engineers at Cefas. Training will include imaging principles, lab measurement, computer vision, ArcGIS, fieldwork, and UAV flying. Applicants should have a UK equivalent Bachelors (Honours) 2:1 in Computer Science, Physics, Maths, or a related numerate discipline, with experience or interest in environmental monitoring, AI, computer vision, or multispectral imaging. English language proficiency (IELTS 6.5 overall, 6 in each category) is required. The studentship is fully funded for eligible UK and international candidates, covering fees, a maintenance stipend (£20,780 p.a. for 2025/26), and a research training and support grant. International students may have the fee difference waived, but relocation and visa costs are not covered. The position is full-time, starting 1 October 2026, with an application deadline of 7 January 2025.

[Funding comprises ‘Home’ tuition fees, an annual tax-free maintenance stipend (2026/27 rate £20,408) for a maximum of 3 years, and £2,000 per annum to support research training activities.] This PhD studentship at the University of East Anglia offers an exciting opportunity to advance automation in aerial imaging for marine litter detection. The project addresses a critical environmental challenge—marine litter—and aims to develop scalable, automated methods for data collection and analysis to better understand sources, pathways, and impacts of litter on ocean health. Supervised by Professor Michal Mackiewicz, the research will build upon existing visible light (VL) deep learning algorithms and extend them to multispectral imaging. Cefas has developed a large training dataset and is establishing a new lab facility to characterize multispectral reflectance of materials. The student will work on developing robust litter detection and classification algorithms, considering the physics of multispectral image formation, including sensor spectral sensitivities, daylight illumination, and material reflectance spectra. The methodology involves utilizing the current VL database, collecting new multispectral data, and training deep learning algorithms to be robust against real-world illumination changes and device variability. Approaches such as device-independent data representations, transfer learning, and domain adaptation will be explored to ensure the algorithms' adaptability to future imaging devices. The student will be based in the Colour & Imaging Lab within the School of Computing Sciences, benefiting from expertise in imaging solutions and opportunities to collaborate with scientists and engineers at Cefas. Training will include imaging principles, lab measurement, computer vision, ArcGIS, fieldwork, and UAV flying. The School of Computing Sciences provides a vibrant research environment, collaborating with multinational companies and research institutes, and is a member of the Turing University Network. Applicants should have a minimum 2:1 degree in Computer Science or a related field, with experience or interest in environmental monitoring, AI, computer vision, or multispectral imaging. The successful candidate will also contribute to laboratory support activities for undergraduate and postgraduate courses in relevant areas. Funding is available for 'Home' tuition fees, an annual tax-free maintenance stipend (£20,408 for 2026/27), and £2,000 per annum for research training activities, for up to three years. The application deadline is 18 June 2026, and the start date is 1 October 2026. To apply, use the University of East Anglia's postgraduate research application portal. Ensure you meet the entry requirements and prepare your CV and supporting documents. For further information, contact the School of Computing Sciences.