- Vacancy Reference Number
- PHD2025
- Closing Date
- 1 Mar 2027
- Salary
- n/a
- Duration
- 4 years
ABOUT THE PROJECT
Understanding how the insect brain functions and generates behaviors is crucial for fields such as ecology, biodiversity conservation, agriculture, pest control, disease prevention and robotics. Advances in computer vision, AI and genetic tools now enable detailed analysis of molecular, cellular and whole-organism behavioral processes, which allow researchers to uncover fundamental biological mechanisms and develop applied solutions.
This PhD project will explore AI-driven analysis of insect behavior and brain function, and will focus on automated tracking, multimodal sensing and advanced computational models to decode how insects perceive, navigate and respond to their environments. The project leverages techniques from computer vision, predictive modeling and image processing to efficiently process large-scale behavioral and sensory data.
There is a wide range of possible research directions for the student to specialise in an area of interest. The projects will be supervised by experts from the departments of Computer Science and Biosciences. All projects have direct relevance to fundamental neuroscience, pollinator conservation and disease vector control. Some examples include:
- Automated Behavior Analysis in Insects: Contributing to behavioral assay development, experimental design and execution of behavioral studies in collaboration with the supervisory team.
- Insect Brain Imaging for Anatomy and Neural Activity Mapping: Focusing on 1) live imaging of neuronal activity in genetically modified mosquitoes, to analyse how insect brains process sensory information, or 2) Imaging of brains of mosquitoes and bees to understand and characterise their brain anatomy and the factors that affect brain development. The images of brains will be obtained either via optical microscopy methods (e.g. confocal microscopy) or with the help of the synchrotron radiation tomography. The student may also contribute to the image acquisition if you wish.
- Multimodal Perception in Pollinators: Investigating how bees and other pollinators integrate visual, olfactory and mechanosensory cues to navigate their environments and interact with their surroundings.
AI for Disease Vector Monitoring and Control: Applying computer vision and machine learning to analyse mosquito behavior, breeding patterns, and responses to repellents to assist in the development of automated monitoring and control systems.
- Neuromorphic Models Inspired by Insect Intelligence: Designing bio-inspired AI systems that mimic insect neural circuits for autonomous robotic perception and navigation for real-time adaptation to complex and dynamic environments.
OUR RESOURCES
Durham University hosts the UK regional supercomputer, Bede, with 128 NVIDIA V100 GPUs. In addition, our the Department of Computer Sciences hosts a NVIDIA CUDA Centre that caters to the increasing GPU demands for research purposes.
Our Computer Sciences laboratories have access to a variety of sensors, LiDAR, RADAR, EEG, drones, robots, cameras, etc.
The Biosciences Department has a wealth of expertise in Ecology, Animal Behaviour, Cell and Molecular biology, Physiology and Neuroscience. The Department has state-of-the-art Bioimaging facilities, equipped with confocal, light-sheet, two-photon and electron microscopes. The Department also has multiple fully equipped molecular biology laboratories and insectaries.
SUPERVISION
You will be supervised by Dr. Amir Atapour-Abarghouei (Personal Website) and Dr. Lena Riabinina (Lab Website), experts in AI-driven perception, insect neuroscience and behavioral analysis.
Dr. Atapour-Abarghouei is an Assistant Professor in Computer Vision and Machine Learning at the Department of Computer Science, Durham University. His research focuses on AI-driven visual perception, multimodal learning and efficient deep learning for real-world applications, with expertise spanning computer vision, robotic autonomy, anomaly detection and AI interpretability.
He has published in top-tier AI venues, including CVPR, ICCV, ECCV, ICML, IEEE Transactions on Image Processing, and IEEE Transactions on Multimedia. His research has significantly impacted areas such as autonomous robotics, AI-driven perception,and computational intelligence. He collaborates with academia, AI research groups, and industry partners on developing next-generation adaptive and efficient AI systems for perception and behavior analysis.
Dr. Riabinina is an Associate Professor in Biosciences at Durham University, specialising in sensory neuroscience, neuroethology and genetic tool development for insect research. She has worked extensively on insect behavior, olfactory processing, visual navigation and brain function, using techniques ranging from AI-based behavioral tracking to advanced imaging and genetic tools. Her previous research spans institutions such as UCL, Johns Hopkins University, Imperial College London and the University of Manchester, where she held a Marie Curie postdoctoral fellowship.
She has published in leading neuroscience and biology journals, including Nature Methods, Current Biology and Nature Communications. Her research has direct applications in pollinator conservation, mosquito-borne disease control and biohybrid robotics.
DURING THE PHD STUDY, YOU WILL RECEIVE:
Regular one-to-one meetings for guidance on research direction, problem-solving, and project development.
Support in publishing high-impact research in both AI and biology-focused journals and conferences.
Interdisciplinary collaboration opportunities, working at the intersection of computer vision, sensory neuroscience and ecology and AI-driven bio-inspired robotics.
Access to cutting-edge experimental and computational resources, including Durham’s GPU clusters, advanced imaging facilities, and insect behavior research labs.
Opportunities to engage with industry and external collaborators, including AI research groups, conservation organisations, and biomedical partners.
Both Dr. Atapour-Abarghouei and Dr. Riabinina have supervised numerous undergraduate, MSc, and PhD students, many of whom have gone on to successful careers in academia, research and industry. Their supervision approach emphasises independent research and interdisciplinary problem-solving, to enable students to develop into highly skilled researchers with expertise in AI, vision-based behaviour analysis and neuroscience and neuroethology.
DURHAM UNIVERSITY
Durham University is a world top-100 university and is ranked the 6th in the UK. As a member university of the elite Russell Group, Durham University focuses on research excellence delivered by world-leading academics. It is the third oldest university in England, following Oxford and Cambridge, with the campus's Cathedral and Castle being a UNESCO world heritage. It is located at Durham in North East England – one of the safest cities in the UK with an affordable living cost.
ENTRY REQUIREMENTS
A relevant undergraduate or master's degree with good scores.
Knowledge of modern programming languages.
Meet Durham's English requirements (https://www.dur.ac.uk/study/international/entry-requirements/english-language-requirements/).
HOW TO APPLY
Please send an email with your resume, transcripts and any supporting documents to Dr. Atapour-Abarghouei at amir.atapour-abarghouei@durham.ac.uk or Dr. Riabinina at olena.riabinina@durham.ac.uk for an initial discussion.
FUNDING NOTES
This is a self-funded PhD position and applications are welcome all year round.
Students of exceptional quality may consider applying for scholarships (including CSC, and Durham University's studentships), which open in November every year. These funding opportunities are extremely competitive.
Further Information
https://www.findaphd.com/phds/project/ai-driven-insect-cognition-computational-models-for-behavior-brain-imaging-and-bio-inspired-robotics/?p182844
Contact Details
Dr. Atapour-Abarghouei at amir.atapour-abarghouei@durham.ac.uk or Dr. Riabinina at olena.riabinina@durham.ac.uk
