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Research Associate: Understanding neural networks (Fixed Term)


We are looking for a Post-doctoral Research Associate to support the research of Professor Allan Herbison whose group is focussed on understanding the neural networks that control puberty and fertility in males and females. In particular, studies will focus on investigating the mechanisms through which kisspeptin neurons control the activity of the gonadotropin-releasing hormone (GnRH) neurons. The role holder will also play a key part in establishing the lab in Cambridge after recent relocation from University of Otago, New Zealand.

You will be involved in establishing and undertaking GCaMP-based single cell (GRIN lens/miniscope) and population (fiber photometry) activity recordings from specific hypothalamic cell populations in freely behaving rodents.

The skills and experience required for the post include: - Ability to undertake and analyse all aspects of GCaMP6/7 fiber photometry and GRIN lens/miniscope investigations of deep brain neural circuits in mice; - Precision stereotaxic surgery skills - Experience with viral vectors for transducing neuronal cells.

You should have a PhD in neuroscience and a strong motivation to lead, conduct and record research at the forefront of neuroendocrinology.

Fixed-term: The funds for this post are available until 31 August 2024 in the first instance.

To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.

Please upload your CV with a list of relevant publications into the online application.

Please quote reference PM17880 on your application and in any correspondence about this vacancy.

The University values diversity and is committed to equality of opportunity.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Further information

Apply online