Job description
This 24-month 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. 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.
The KTP Associate will:
• Work with stakeholders, including senior leaders, MOA commercial, sales
and marketing functions, academic experts and MOA technical
multi-disciplinary scientists, developing networks across the business to
understand project requirements and deliverables.
• Develop understanding of the highly regulated herbicide industry and
needs of current MoA customers.
• Determine technical scope, objectives, specification and opportunities
for technology advancement.
• Experiment with complex artificial intelligence methods that consider
the range and influence of independent variables, interactions and
interdependencies.
• Develop novel artificial intelligence (AI) solutions to acquire and
analyse high-quality data from herbicide-treated plants and controls.
• Assess available archived image data for suitability to analyse and
detect treatment effects with the required specificity sensitivity and
accuracy for the detection across the range of expected symptomologies.
• Develop deep-learning models, robust/fast learning algorithms, and
databases/data warehouses satisfying quality performance indicators.
Delivering protocols and workflows to enable testing and validation across
future-users.
• Produce and deliver reports to the senior management team and employees
across MOA business functions at different organisational levels.
• Provide training materials/workshops to MOA employees, collaborators
and customers.
Project description
Development of an automated AI weed and growth inspector for safe and effective herbicide development.
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.
About the business
Established in 2017 MOA Technology Ltd are a small science led company at the forefront of ethical and sustainable crop protection (https://www.moa-technology.com/). Their highly experienced leadership team comes from across industry, science, technology and academia to drive innovation. MOA aims to solve an urgent global problem with new mode of action herbicides that: • respect human and environmental health • support farmers with products to face the food supply challenge safely, consistently and efficiently • advance the industry with a collaborative approach to sustainable integrated weed management
Higher Education
Artificial Intelligence, Computer Science
MSc/PhD degree in Computer Science or related subjects, or BSc with required experience
13 June 2022
3 July 2022
3 July 2022
REQ220684
This 24-month 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. 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.
The KTP Associate will:
• Work with stakeholders, including senior leaders, MOA commercial, sales and marketing functions, academic experts and MOA technical multi-disciplinary scientists, developing networks across the business to understand project requirements and deliverables.
• Develop understanding of the highly regulated herbicide industry and needs of current MoA customers.
• Determine technical scope, objectives, specification and opportunities for technology advancement.
• Experiment with complex artificial intelligence methods that consider the range and influence of independent variables, interactions and interdependencies.
• Develop novel artificial intelligence (AI) solutions to acquire and analyse high-quality data from herbicide-treated plants and controls.
• Assess available archived image data for suitability to analyse and detect treatment effects with the required specificity sensitivity and accuracy for the detection across the range of expected symptomologies.
• Develop deep-learning models, robust/fast learning algorithms, and databases/data warehouses satisfying quality performance indicators. Delivering protocols and workflows to enable testing and validation across future-users.
• Produce and deliver reports to the senior management team and employees across MOA business functions at different organisational levels.
• Provide training materials/workshops to MOA employees, collaborators and customers.