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4 months ago

United Kingdom Phytoform Full time

Data Scientist for Phytoform Labs Ltd
At Phytoform Labs, we believe in sustainable agriculture and nutrition for all. We see a lack of innovation in the agricultural space around the crops themselves, so we are building a multidisciplinary team to help rectify the situation. We have exciting growth plans over the next year and we are looking for a talented Data Scientist to join our computational team and help mature CRE.We are based at the world-leading plant science institute Rothamsted Research just outside of London, United Kingdom.

You will be working within the computational team, under the guidance of the Lead Data Scientist, to develop machine learning models for understanding the fundamental rules in plant genetics. Successful projects will be highly scalable and automated across a wide range of species, and results will be taken on by the wetlab team to be bred into new varieties, ultimately developing better crops.

As a Data Scientist at Phytoform, you have the rare opportunity to be part of the full data cycle: training our model on publicly available and in-house data, deploying it to generate predictions for the wet lab to validate, then feeding the new validated data back into the model, all the while having the opportunity to contribute to improving both the AI model and the laboratory processes.

Implement and test machine learning models
● Design innovative solutions for improving performance
● You will have at least a PhD or two years industry experience in a relevant technical field
● Proficiency in the python programming language, and the ability to write good code according to software development best practices
● Experience coding in a team using git version control and writing tests
● Familiarity with the Linux operating system
● Fluent in the core machine learning concepts, as well as training and optimising neural network models
● Have a working knowledge of C / C++
● Are familiar with AWS machine learning services
● Competitive salary.
● Private medical insurance.
● A flexible working arrangement: early or late working with core hours of 10am-4pm.
● Working from home arrangement.
● Cycle to work scheme.