Role Purpose:
Help drive the invention of safe and sustainable active ingredients and understand product performance through predictive modelling and biological data analysis.
About this Opportunity:
At Syngenta Crop Protection, there has been significant focus and investment in predictive science and digital transformation throughout our research and development pipeline. From exploiting new digital technologies in the lab to extracting maximum value from existing knowledge, data- and model-driven decision making are changing the way we do science and develop new solutions for sustainable food production.
The focus area for this role is to provide predictive modelling support to understand biological efficacy and other aspects of product performance in field trials and controlled environments.
Depending on the problem, you will use data-driven and/or mechanistic modelling approaches to understand complex factors such as environmental conditions, crop varieties, pests and transport processes in soil and the plant, and how they relate to endpoints such as crop yield and efficacy on the pest. Working alongside multidisciplinary project teams, you will identify opportunities where models can add value, investigate innovative approaches, and drive strategic initiatives to make better decisions more quickly. You will also provide guidance to other scientists on experimentation and better trial design for modelling purposes, and work with software developers to make model-based approaches scalable and easy to use for other scientists.
Building on your passion for science and innovation, you will join an active network of data experts and specialist data modelers at Syngenta to champion the use of predictive models and digital thinking.
Accountabilities
- Works in multidisciplinary project teams to bring data analytics and modelling skills to the discovery, optimization and development of crop protection leads or product candidates
- Interacts with domain experts to understand scientific problems and identify opportunities where the adoption of models will drive value for the business
- Works with colleagues in adjacent fields of predictive science to investigate interdisciplinary and multiscale modelling approaches to solve fundamental challenges in active ingredient development for crop protection
- Drives strategic business initiatives across Crop Protection R&D e.g. working with physical chemistry, biokinetic and environmental data to model laboratory, glasshouse and field trials.
- Provides expertise and guidance to scientists in the design of experiments and field trials for modelling purposes
- Works with R&D IT and software developers to build data connections and deploy customer facing applications
- Merges data from multiple data sources together to prepare them for analysis
- Monitors new developments in the field and maintains awareness of modelling approaches taken by other companies, vendors, and academia. Explores new analytical tools, methodologies or approaches to understand their effectiveness and how to deploy them
- Works with external collaborators to understand and integrate their complementary capabilities into projects and programs
Qualifications
Knowledge, Skills & Qualifications
- Strong academic foundation in predictive modelling preferably to PhD/Masters level in Natural Sciences PhD (ecology, env. science, biology or chemistry)
- Knowledge of relevant data-science, analytics and modelling tooling (e.g. Python, R, Matlab, etc.)
- Scientific domain knowledge in relevant field such as biology, chemistry, environmental science etc.
- Ability to acquire domain knowledge in adjacent scientific areas to effectively work across internal teams and quickly get up to speed with existing modelling opportunities
- Experience in developing models relevant to biological outcomes (e.g., ecological modelling, ecotoxicology, environmental fate, epidemiology, disease modelling, PKPD)
- Strong analytical thinking and problem-solving skills, adaptability to different business challenges and data sources, as well as curiosity and openness to new solutions.
Additional Information
In return for your skills and knowledge Syngenta will offer:
A variety of financial and non-financial benefits including:
- You will profit from a competitive pension fund plan, attractive bonus system, onsite doctor, fitness room, canteen, and other benefits (Family friendly initiatives, Child and Family allowance…)
- We offer a position which contributes to valuable and impactful work in a stimulating and international environment
- The opportunity to work with and learn from highly qualified and experienced employees and gain scientific and technical excellence
- Learning culture (Together we Grow) and wide range of training options
Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.
https://www.syngenta.com/careers/working-syngenta/diversity-and-inclusion
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Company Description
Modelling Scientist, Crop Protection
Basel, Switzerland Or Jealotts Hill, United Kingdom
(We are hiring several Modelling Scientist/ Senior Modelling Scientist who can be based in either Basel Switzerland OR Jealotts Hill, UK)
About Syngenta:
Syngenta is a leading agrochemicals company; dedicated to bringing plant potential to life. Each of our 30,000 employees in more than 100 countries countries works together to solve one of humanity’s most pressing challenges: growing more food with fewer resources. From the moment a seed is planted through to harvest, crops need to be protected from weeds, insects, and diseases as well as droughts and floods, heat, and cold. As a world market leader in crop protection, we help farmers to counter these threats and ensure enough safe, nutritious, affordable food for all – while minimizing the use of land and other agricultural inputs. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture.
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