JOB: KTP Associate: Precision Agriculture Data Scientist
The UCL Department of Statistical Science, in partnership with Hummingbird Technologies Limited, is offering a unique opportunity to work with two prestigious organisations on a project to improve the science, collection protocol, dataset quality and analysis behind Hummingbird's machine learning capabilities to achieve a +95% accuracy on their presymptomatic disease and weed detection algorithms to create commercially scalable products in line with Hummingbird's vision. The Knowledge Transfer Partnership (KTP) will address how to understand and improve data collection for crop health via field visits, and to research, develop and integrate models and tools within the Hummingbird software platform.
The post holder will draw up a supervisory agreement in consultation with the project investigator and will then be responsible for the day to day running of the project. They will develop the business research and keep the project supervisors informed of the progress at regular meetings, as well as disseminating outcomes from the project through internal and external conferences and journal papers.
The post is available immediately and is funded for two years in the first instance. Salary is Grade 6: 30,316-31,967 GBP per annum or Grade 7: 34,635-41,864 GBP per annum. Appointments at either grade qualify for a £4,000 dedicated personal development budget and £7,500 for travel and consumables.
For appointment at Grade 6, candidates should hold an MSc (or equivalent qualification) in Data Science (Big Data Analytics, Machine Learning or closely related subject), Statistics, Engineering or Mathematics, combined with specific relevant industry experience. For appointment at Grade 7, candidates should hold or be close to submitting a PhD (or equivalent qualification) in Machine Learning/ Image Analysis/ Pattern Recognition/ Applied Statistics/ Data Science or closely related subject. It is essential that the successful candidate has experience in statistical modelling and analysis, and applied machine learning methodology with demonstrable skills in the use of RNN/LSTM, CNN and ensemble learning approaches; programming experience in Python adequate for data science research; and strong analytical, problem solving and communication skills.
Further particulars including a job description, person specification and details of how to apply can be accessed at http://www.ucl.ac.uk/statistics/department/jobs. Informal enquiries may be addressed to Dr Jinghao Xue, email: [log in to unmask], tel: +44(0)20 7679 1863.
Closing date: 23 May 2018
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