Syngenta Crop Protection is a leader in agricultural innovation, bringing breakthrough technologies and solutions that enable farmers to grow productively and sustainably. We offer a leading portfolio of crop protection solutions for plant and soil health, as well as digital solutions that transform the decision-making capabilities of farmers. Our 17,900 employees serve to advance agriculture in more than 90 countries around the world. Syngenta Crop Protection is headquartered in Basel, Switzerland, and is part of the Syngenta Group.

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Our Site:

Jealott's Hill International Research Centre is situated in pleasant semi-rural surroundings between Bracknell and Maidenhead and is the place of work for approximately 800 Syngenta scientists and support staff. Jealott’s Hill is one of the main global research and development sites and key activities include research into discovery of new active ingredients, new formulation technologies, product safety, technical support of our product range and seeds research.

Syngenta’s Crop Protection Bioscience function contributes to the innovation of safe crop protection agents through a deep understanding of biology, mode of action, resistance mechanisms and ADME that is used to improve product performance and sustainability. We collect a wide range of data across Bioscience and our digital group employs a combination of image processing, statistical, artificial intelligence, and machine learning techniques to support data-driven decision making. A large component of the work is the design of complex experiments, the integration of heterogenous data sources, and the knowledge extraction.  If you are passionate about delivering computational solutions that will help Syngenta create products which can feed the world sustainably, we have the job for you.

Role Overview:

In Crop Protection Bioscience, we are looking for a driven, 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 experimental scientific data to generate models that derive new insights to support advances in bioscience research programs. You will focus on the development and deployment of algorithms, establish ETL (Extract, Transform, Load) pipelines, build visualizations, and communicate statistical outcomes to a general audience. Successful applicants will become part of the data science community within Syngenta and contribute models to Syngenta's predictive modelling platform.

Accountabilities

• Understand the Bioscience data landscape, key data attributes and experimental capabilities to identify opportunities for enabling and enhancing our science through the deployment of analytical methods and predictive models.
• Identify data needs and provide recommendations to scientists to ensure data integrity
• Research, apply and build state of the art machine learning and other data-driven approaches to address Crop Protection challenges
• Evaluate algorithm performance, assess model assumptions and their uncertainty, and effectively communicate findings to technical and non-technical audiences
• Work collaboratively as part of the Bioscience Digital group and the wider data community to deliver and deploy new models, share learning, new methods and technologies and drive innovation in digital and data science.

Education & Experience 

MSc/PhD (or equivalent experience) in natural sciences with focus on analysis of data and data integration, data science and/or machine learning. Postdoctoral experience in life sciences research or experience in an R&D environment would be a plus.

Required Skills

• Enthusiasm for extracting and communicating knowledge from data
• Dynamic personality with passion for innovation and problem-solving
• Experience in building mathematical models A good understanding of experimentally derived biological data, data types and appropriate analytical methods and fundamental statistical concepts
• Ability to work in multi-functional teams
• Thorough understanding and hands-on experience with the standard R and Python data science stack, including libraries used for data cleaning, modelling, visualization, and machine learning
• Understanding of data-driven web apps and corresponding tooling, e.g. Plotly/Dash and R shiny, including deployment
• Familiarity with relational and non-relational databases including graph databases and understanding of good data management practices for scientific data
• Understanding and adherence to recommended best practices for software development in a team environment
• Fundamental understanding of deep learning techniques
• Proficiency in both written and verbal communication skills
• Ability to manage and contribute to projects autonomously
• Experience with version control systems and creating reproducible digital workflows

Desirable skills

• Experience in building mechanistic models
• Experience in building data models and database management
• Experience in building ADME models
• Knowledge in Cell Biology, Entomology, Phytopathology, Developmental Biology
• Experience with object-oriented programming

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

Did you know? Syngenta has been ranked as a top employer by Science Journal