Scientist Computational Biology

Drive data-driven discovery in crop protection by applying advanced computational approaches to solve complex biological challenges. In this role, you will collaborate with scientists across Crop Protection Research, developing and deploying bioinformatics tools, machine learning models, and data workflows that generate insights from diverse biological datasets—directly supporting the development of safer, more sustainable agricultural solutions. Key Responsibilities - Develop and apply state-of-the-art computational methods to address key challenges in Crop Protection Bioscience. - Design, test, and deploy data analysis tools, workflows, and modelling approaches using iterative, evidence-based methods. - Communicate analytical results, insights, and recommendations clearly to both technical and non-technical audiences. - Guide scientists on data quality, integrity, and suitability for analysis. - Collaborate across the Bioscience Digital team and wider R&D data community to share learning and drive innovation. - Monitor external scientific and computational developments and identify opportunities for application within Bioscience. - MSc/PhD in computational biology, data science, natural sciences, or a related discipline, with a focus on data analysis, machine learning, or multi-omics data integration. - Strong hands-on experience with Python and R for bioinformatics, data analysis, and visualisation. - Confidence building, validating, and testing machine learning models. - Experience with high-performance computing, version control systems, and reproducible digital workflows. - Ability to work autonomously and communicate effectively with researchers across diverse scientific disciplines. - Enthusiasm for innovation and solving complex biological problems through computational approaches.