The successful candidate will serve as a Cheminformatics Scientist in our Predictive Safety Center within Crop Protection Regulatory Sciences with responsibilities in the designing and screening of new active ingredients and products in the discovery phase; this includes: Developing and applying of various models (QSAR, pharmacophore, etc.) to predict hazard and exposure endpoints and direct testing strategy for safety assessment of discovery molecules; Applying modern computational methods to develop QSAR relationships and predictive ADMET technologies for multi-parameter optimization of discovery-phase molecules; Evaluating and validating external software and models for the application within the agrochemical sector; Designing and developing in silico methods for safety assessment of discovery molecules using existing internal and external datasets; Creating methodologies to integrate large data sets to investigate linkages between toxicological and ecotoxicological adverse effects and chemical structure and sub-sturcutre; Developing a relational context between likely moieties and chemical structure and sub-structures). Collaborating with internal computational chemists and data scientists, academia, government, and industrial partners to explore and implement new in silico capabilities; Developing and managing a variety of cheminformatics databases related to the needs of human health and environmental safety assessment; Partnering with and guiding scientists in the use of predictive computational and cheminformatics tools for analog screening. Qualifications Requirements: PhD in computational chemistry, cheminformatics, or related discipline with 3+ years of post-doctoral and/or industrial experience in QSAR modeling and Read-Across; Advanced knowledge of cheminformatics principles, computational chemistry, and their application to agricultural or pharmaceutical discovery projects; Experience with Pipeline Pilot and/or KNIME in cheminformatics and QSAR; Experience in cheminformatics database management; Proficiency in small molecule ligand discovery and cheminformatics techniques including molecular modeling, docking, pharmacophore modeling, QSAR, clustering, fingerprint & shape-based database search, and virtual screening; Strong hands-on experience with molecular modeling suites such as MOE, Discovery Studio, ADMET Predictor and Schrodinger; Working knowledge of modern techniques and approaches in statistical modeling, machine learning, and data visualization. Strong written and oral communication skills that allow dissemination of complex technical issues in a clear, concise manner to a variety of scientific and non-scientific audiences; Keen interest in working in a dynamic, exciting industry and applying scientific information for protection of human and environmental health. Preferences: Proficiency in programming with Python, R or Javascript is a plus Who are we, and what do we do? At Corteva Agriscience, you will help us grow what’s next. No matter your role, you will be part of a team that is building the future of agriculture – leading breakthroughs in the innovation and application of science and technology that will better the lives of people all over the world and fuel the progress of humankind.
