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Development of an automated AI weed and growth inspector for safe and effective herbicide development.
This 24-month project between Loughborough University and MOA Technology Ltd is joint funded with UKRI Innovate UK. KTPs aim to help businesses improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK Knowledge Base.
MoA Technology have developed an innovative approach to commercialise new herbicidal compounds with unrivalled effectiveness and safety. Through their expertise in plant sciences MOA have combined their unique herbicidal compound library with a multi-stage discovery screening platform. This revolutionary approach has uncovered herbicidal modes of action (MOA) that overcome herbicide resistance and environmental impacts. Whole plant herbicide impact and performance testing represent a vital stage in bringing herbicidal compounds to market ensuring high-yielding, safe food production.
This KTP will support commercial delivery of effective herbicides by developing an automated Artificial Intelligence (AI) inspector for data collection, collation and analysis of new compounds screening in whole plant glasshouse scale efficacy and toxicology trials.
The successful candidate will be a highly motivated individual with formal qualifications in computer science or related subjects at MSc/PhD level or BSc with required experience. They will have experience in computer vision, machine learning, deep learning and image processing methods including data cleaning and migration. Analytical by nature, the successful applicant will have excellent knowledge of analytical techniques with experience in algorithm and software development. Candidates should have demonstrable programming skills e.g. Python, C++ and experience in deep learning platforms (e.g. PyTorch, TensorFlow).
The KTP Associate will be based primarily at the Company premises in the Magdalen Centre, Oxford Business Park, Oxfordshire OX4 4GA, and will also spend time at Loughborough University with the academic team.
Informal enquiries should be made to Prof. Baihua Li email@example.com )
Position type: Contract full-time - 37.5 hours per week
Location: The Oxford Science Park and Loughborough University,
The closing date for receipt of applications is Sunday 3rd July 2022
Interviews will be held on Monday 18th and Tuesday 1 July 2022
Please follow this link for details
Job profile (lboro.ac.uk)
Must be legally able to live and work in the UK