A Research Assistant post is available in the Drosophila Connectomics Group directed by Greg Jefferis and Matthias Landgraf in the Department of Zoology at the University of Cambridge.
Applicants will work with electron-microscopy image data, annotate and proof-read automatically segmented reconstructions of neurons and their connectivity, develop open source tools for data analysis/processing and perform neuron morphology, graph/circuit analyses etc. to obtain biological insight. A background in neurobiology or a strong quantitative preparation (e.g. in bioinformatics/computer science) will be helpful.
Successful candidates will join a team based in Zoology with 16 team members, carrying out data processing and computational analysis of neuronal reconstruction data. They will interact closely with a similar team in the US as well as experimental groups in Oxford (Scott Waddell) and Cambridge (Greg Jefferis). Candidates will need to be highly motivated and develop a good understanding of the nature of the data and the scientific aims of the project. This will be critical to setting priorities as the project develops. Close teamwork and a collaborative spirit will be essential, but team members will have increasing opportunities for scientific independence as their expertise develops. Candidates will report to a team leader based in Zoology and will be mentored by an experienced post-doc. There will be opportunities to contribute to training new team members as the group expands and to general project management, as well as to participate in public engagement activities.
The role will be based on site in the Department of Zoology, with hybrid working arrangements possible following agreement.
Please upload a copy of your CV (2 sides of A4 maximum) and a covering letter (2 sides of A4 maximum).
Interview dates: Interview between 4th and 5th January 2023 - may be conducted remotely.
Fixed-term: The funds for this post are available for two years with a possibility of extension subject to project status and funding
Flexible working requests will be considered.
We particularly welcome applications from women and /or candidates from a BME background for this vacancy as they are currently under-represented at this level in our University.
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