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Neural Circuit Function in the Olfactory Bulb

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  • Full or part time
    Dr J. Johnston
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Applications are invited for a Ph.D. studentship in the lab of Dr. Jamie Johnston based in the School of Biomedical Sciences at the University of Leeds. The project will investigate the neural circuitry of the olfactory bulb.

The primary function of the olfactory system is to detect and classify odourants. This is achieved by an odourant binding and activating a particular set of olfactory receptor neurons. How the olfactory system categorises such patterns of neural activity into different odours is still unclear. This computation of “pattern recognition” is a general problem faced by the brain, occurring across sensory modalities and in many forms e.g., facial and speech recognition. As pattern recognition is a primary function of the olfactory system, it is an ideal place to study how this computation is implemented by neural circuitry. The project will focus on the olfactory bulb, the first circuit in the olfactory system, and will investigate how the circuits output encodes different input patterns and what aspects of the circuit change during learning.

The applicant will acquire a range of cutting-edge physiological techniques to analyse the function of neural circuits. The project will employ optogenetic and odour stimulation to probe the input to the olfactory bulb while multi-photon imaging and/or electrophysiology will measure the circuit’s output. A key aspect of this project will be the development of computational models of the olfactory circuitry, the models will guide and be tested by experiment.

We are seeking a talented and highly motivated individual with a strong interest in neuroscience. The successful applicant will have some research experience and achieved a first or upper second-class honours degree in neuroscience, physiology or a related discipline. Applications from engineering, computer science, physics and maths graduates are also encouraged. Some experience with programming (e.g. Python, Igor Pro, Matlab or similar) will be highly advantageous.

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