Research Associate (Fixed term - two positions available)
Milner Therapeutics Institute, University of Cambridge
The Functional Genomics Screening Laboratory (FGSL), located at the Milner Therapeutics Institute, is seeking two research associates to perform high-throughput CRISPR phenotypic screening in complex models.
Salary: £37,174-£45,413
About the FGSL:
The FGSL is a partnership between the Milner Therapeutics Institute (MTI), the Medical Research Council and AstraZeneca. The newly established lab, located in the MTI, aims to accelerate novel target discovery in health and disease through CRISPR screening. Leveraging arrayed screening to systematically perturb individual genes in a microtitre plate format, the FGSL forms cross-functional partnerships to interrogate the genome at scale.
Key responsibilities:
Working closely in a team, the post holder will design and implement arrayed CRISPR screens in human cellular models. This will include primary cells, stem-cells, co-cultures or organoids in non-oncology research areas. Working with academic and industry collaborators across the UK, the successful candidate will scope and optimise a range of functional assays such as high-content imaging, flow cytometry or ELISAs to characterise the phenotypic changes upon CRISPR editing. The role will involve designing and performing high-throughput screening workflows that encompass gene editing, phenotypic assays and automated liquid handlers.
Why join us?
The MTI offers a buoyant, vibrant, and fast-paced environment that fits individuals who thrive amidst change and innovation. As part of our team, you will work at the dynamic interface between academia and industry, engaging with researchers from diverse sectors to foster knowledge exchange and drive pioneering functional genomics research.
You will be part of an engaging and supportive environment that prioritises professional growth and career development. The role offers the unique opportunity to enhance a variety of transferable scientific skills such as culturing and perturbing complex cell models, applying laboratory automation in biological experiments, and analysing multi-parametric data to support phenotypic-driven target discovery.
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