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Job Location | London |
Education | Not Mentioned |
Salary | £50,000 - £60,000 per annum |
Industry | Not Mentioned |
Functional Area | Not Mentioned |
Job Type | Permanent , full-time |
£50-60k salary + equity + benefits!LondonHybrid workingThis start-up are on a mission to revolutionise the worlds food sources. Picture yourself at the forefront of a groundbreaking agbiotech startup, using cutting-edge computational methods to accelerate the development of more sustainable, nutritious, andclimate-resilient crops. Theyre building the worlds first ML-driven target discovery platform for crop gene-editing, and need your expertise to take it to the next level!What sets them apartInspired by advancements in drug discovery, their talented team harnesses the power of deep learning, transformers, and graph-based technologies to identify high-value genetic targets for crop gene-editing. Join them in making a global impact on plant sciences,food security, and the environment.What are they looking for you to accomplishYoull be part of their small Bioinformatics Team, working hand-in-hand with the CTO and Principal Bioinformatician to identify and refine appropriate data inputs for knowledge graphs. Beyond this, youll have the opportunity to support on data engineeringand ML workflows, working cross-functionally to gain broad experience across computational biology activities.This is the perfect opportunity for an ambitious biology (post)grad looking for an impactful, dynamic and multi-faceted engineering role in biotech. The position offers the chance to be at the forefront of a truly global and transformative mission, usingstate-of-the-art computational methods, within a fast-growing agbiotech startup. They are poised for significant growth. As we move towards future funding rounds we envision the role growing with the company, offering leadership opportunities as we scale.If youre passionate about bioinformatics, plant sciences, food security and impact, wed love to hear from you!Bioinformatician Responsibilities:
Keyskills :
data analysisbioinformaticspipelines