CPR Biology computer vision scientist

Company Description

Syngenta’s Crop Protection Bioscience and Biology functions contribute to the innovation of safe crop protection agents and plant health enhancers through a deep understanding of biology, mode of action, resistance mechanisms and ADME that is used to improve product performance and sustainability. In the Bioscience and Biology Digital teams, we use a combination of data science, image processing and machine learning techniques to explore new ways of deriving knowledge from experimental endpoints and digital phenotypes that include multi-dimensional image, mass spectrometry, biochemical assay and genetic data. A large component of the work is the application of computer vision to our phenotyping assessments.  If you are passionate about Biological applications of computer vision and keen to deliver solutions that will help Syngenta to create products which can feed the world sustainably, we have the job for you.

Job Description

Role description

The Crop Protection Biology digital team is looking for a driven and innovative individual to collaborate with scientists across the Crop Protection business to build a vision of how to approach future challenges in crop health management using a digital first mindset. You will use your experience in the analysis of digital image data to generate models that derive new insights to support biological screening platforms and experimental programs. You will focus on the development and deployment of creative and unique algorithmic models, establishing analysis pipelines, ensuring model validity and functionality and teaching individual scientists how to use them. Successful applicants will become part of the digital and data science community within Syngenta and contribute models to Syngenta's modelling platform, PRIME.

Accountabilities:

• Learn and understand the Biology & Bioscience data landscape, key data attributes and experimental capabilities to identify opportunities for enabling and enhancing our science through the deployment of digital imaging technologies and analyses
• Identify data needs and provide recommendations to scientists to ensure the quantity and verify the integrity of image data used for analyses through the application for statistical methods
• Research with support of computer vision technical experts and apply state of the art machine learning and other data-driven approaches to address Crop Protection challenges through the application of digital imaging
• Evaluate algorithm performance—validate findings using a trial and iterative approach and effectively communicate findings to technical and non-technical audiences
• Work collaboratively as part of the Crop Protection digital community to deliver and deploy new models, share learning, new methods and technologies and drive innovation in digital and data science

Qualifications

Education & experience

MSc in Computer science with a on focus on image processing, data science and/or machine learning. PhD experience in life sciences research or experience in an R&D environment would be a plus.

Required Skills

• knowledge of image analysis procedures for the quantitative extraction of traits from remote and proximal sensing systems (2D and 3D) including machine-learning (classifiers, clustering, feature selection/reduction, dimensionality reduction) and deep learning-based algorithms
• A good understanding of experimentally derived biological data, data types and appropriate analytical methods, fundamental statistical concepts including multivariate analysis
• Thorough understanding and hands-on experience with the standard R/Python data science stack, including libraries used for data cleaning, modelling, visualization, and standard machine learning frameworks
• Dynamic personality with passion for innovation and problem-solving
• Ability to work in multi-functional teams
• Proficiency in both written and verbal communication skills
• Ability to manage and contribute to projects autonomously
• Experience with version control systems, notebooks and creating reproducible digital workflows

Desirable skills:

• Demonstrated coding ability in Python, Bash and C++ and open-source software including ImageJ, OpenCV, Tensorflow and Pytorch
• Sound understating of Hyperspectral imaging, Augmented Reality, Sensor Analytics, GIS environments would all be beneficial
• Knowledge of fundamental concepts in imaging-based automated plant phenotyping, statistics and bioinformatics including biological databases and web tools
• Understanding of data-driven web apps and corresponding tooling, e.g. Plotly/Dash, Flask and Shiny
• Knowledge in Cell Biology, Entomology, Phytopathology, Developmental Biology

Additional Information

In return for your skills and knowledge Syngenta will offer:

• Competitive benefits package including opportunities for flexible working.
• Up to 31.5 days annual holiday.
• Interaction with external researchers and opportunities to represent Syngenta in research networks, collaborations and conferences.
• Good onsite facilities including a staff restaurant, a gym and fitness classes.
• Campus environment based at Jealott’s Hill located in the Berkshire countryside between Bracknell and Maidenhead.
• Great opportunities for personal and career development.
• A modern, stimulating and dynamic working environment which promotes diversity and inclusion, scientific excellence and collaboration.
• A job and responsibilities with purpose at state-of-the-art facilities within a world class R&D campus site.

We embrace and encourage diversity, and this is what drives our innovation and lets us outperform the market. https://www.syngenta.com/careers/working-syngenta/diversity-and-inclusion

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