The successful candidate will be responsible for the discovery and optimization of small molecule leads for crop protection, pest, and vegetation management in a collaborative effort with chemists, biologists, process chemists, and numerous other disciplines. The selected candidate will develop and utilize innovative computational techniques for the hit-to-lead discovery process and lead optimization problems in association with scientific teams.

What You’ll Do:

• You will be involved in structure-based (SB) and ligand-based (LB) drug design, compound selection and acquisition, HTS data analysis and triage, virtual screening, statistical modeling, and ADMET prediction. You will be collaborating closely with chemists, biologists, scientists, and other project team members to generate and test novel hypotheses and cross-collaborate with Crop Protection Discovery/Development teams for advancing the study of new pipeline areas of research.

• You will also have the opportunity to participate in evaluating, developing, implementing, and applying new computational methodologies and strategies.

• You will identify areas of scientific improvement within computational sciences and their potential for application to projects.

• You will contribute to the development of new computational capabilities and maintain an up-to-date awareness of recent literature and current developments within the field and generate, document, and communicate research in the form of internal scientific reports and external publications.

What Skills You Need:

• A Ph.D. degree with experience in a relevant discipline: computational chemistry, computer-aided drug design.

• A track record of scientific innovation, as demonstrated by publications, or presentations.

• Expertise in ligand- and structure-based drug design, with experience in common molecular modeling techniques (MD simulations, QSAR models, quantum mechanics (QM) methods, protein homology modeling, Docking, pharmacophore modeling, Ligand/Structure-based virtual screening.

• Knowledge-based methodologies and selecting appropriate methods towards hit identification and optimization.

• Expertise in at least one of the following techniques is a plus: ADMET and physicochemical property prediction, machine learning, Programming scripting, and good knowledge of Linux would be an advantage.

• Effective communication and presentation skills, capable of conveying technical and project information in a clear manner.

• Keep in mind, equivalent amounts of relevant experience may be considered in lieu of the above requirements