SELF-FUNDED PhD: AI-Driven Insect Cognition: Computational Models for Behavior, Brain Imaging a[...]

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SELF-FUNDED PhD: AI-Driven Insect Cognition: Computational Models for Behavior, Brain Imaging and Bio-Inspired Robotics

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, focusing 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 specialize 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:

1. Automated Behavior Analysis in Insects: Contributing to behavioral assay development, experimental design, and execution of behavioral studies in collaboration with the supervisory team.
2. Insect Brain Imaging for Anatomy and Neural Activity Mapping: Focusing on live imaging of neuronal activity in genetically modified mosquitoes, and imaging of brains of mosquitoes and bees to understand their brain anatomy.
3. Multimodal Perception in Pollinators: Investigating how bees and other pollinators integrate visual, olfactory, and mechanosensory cues.
4. AI for Disease Vector Monitoring and Control: Applying computer vision and machine learning to analyze mosquito behavior and breeding patterns.
5. Neuromorphic Models Inspired by Insect Intelligence: Designing bio-inspired AI systems that mimic insect neural circuits for autonomous robotic perception.

OUR RESOURCES
Durham University hosts the UK regional supercomputer, Bede, with 128 NVIDIA V100 GPUs. The Department of Computer Sciences hosts a NVIDIA CUDA Centre that caters to the increasing GPU demands for research purposes. Our laboratories have access to a variety of sensors, LiDAR, RADAR, EEG, drones, robots, and cameras. The Biosciences Department has state-of-the-art Bioimaging facilities and multiple fully equipped molecular biology laboratories.

SUPERVISION
You will be supervised by Dr. Amir Atapour-Abarghouei and Dr. Lena Riabinina, experts in AI-driven perception, insect neuroscience, and behavioral analysis.

DURING THE PHD STUDY, YOU WILL RECEIVE:
- Regular one-to-one meetings for guidance on research direction.
- Support in publishing high-impact research.
- Interdisciplinary collaboration opportunities.
- Access to cutting-edge experimental and computational resources.
- Opportunities to engage with industry and external collaborators.

DURHAM UNIVERSITY
Durham University is a world top-100 university and is ranked 6th in the UK. It focuses on research excellence delivered by world-leading academics.

ENTRY REQUIREMENTS
- A relevant undergraduate or master's degree with good scores.
- Knowledge of modern programming languages.
- Meet Durham's English requirements.

HOW TO APPLY
Please send an email with your resume, transcripts, and any supporting documents to Dr. Atapour-Abarghouei or Dr. Riabinina for an initial discussion.

FUNDING NOTES
This is a self-funded PhD position. Applications are welcome all year round. Students of exceptional quality may consider applying for scholarships.

Further Information

Project Link

Contact Details

Dr. Atapour-Abarghouei at amir.atapour-abarghouei@durham.ac.uk or Dr. Riabinina at olena.riabinina@durham.ac.uk