Computational Chemistry/Toxicology Scientist

Computational Chemistry/Toxicology Scientist#25-57298

Indianapolis, IN

All On-site

Job Description

This position is located in Indianapolis, IN, we are only looking for local candidates to Indy at this time.

Any specific skills, requirements or experience you want in a candidate: Computational Chemistry skills; PH.D Required - Chemistry, Toxicology, Cheminformatics

Our Client has an exciting and challenging opportunity for a Computational Scientist Contractor with expertise in Cheminformatics/Bioinformatics. The individual will partner with a multidisciplinary team to design, develop, and implement machine learning models to predict safety profiles of chemicals to support the discovery, development and registration of Client crop protection products.

Responsibilities:

Develop and apply chemistry structure-based predictive models for assessing safety profiles of early-stage discovery molecules

Assess potential mechanisms of toxicity by assessing ligand-protein binding affinity using protein structure alignment, binding pocket evaluation, and molecular docking

Work collaboratively with internal and external cross-functional multidisciplinary teams, collaborators, and consultants to implement in silico models to meet business needs

Serve as a subject matter expert on in silico modelling for the team and other partners in R D sub-functions

Present the development and application of cheminformatics/bioinformatics approaches and Client ML/DL models internally and externally including scientific conferences

Keep abreast of the latest scientific development in the areas of machine learning, cheminformatics, bioinformatics, and related fields and identify technologies to be applied internally

Analyze complex datasets using machine learning approaches and interpret results to improve data-driven decision-making processes

Qualifications:

Ph.D. degree in Cheminformatics, Computational Chemistry, Computational Biology, Bioinformatics, Toxicology, or a related field

3+ years of experience in developing machine learning models and applying cheminformatics/bioinformatics and AI for structure-based drug design, toxicology assessment, mechanism prediction

Strong technical background in machine learning, deep learning, and statistical modeling with prior experience in applying these techniques to process, analyze and draw insights from complex datasets involving chemical compound structures and toxicity endpoints

Demonstrated programming proficiency in Python and experience in utilizing machine learning libraries

Demonstrated in-depth knowledge in toxicology, chemistry, chemical structure, QSAR, protein structure

Knowledge in omics analysis and systems biology is a plus

Demonstrated teamwork and project leadership skills to manage multiple projects on different timelines for stakeholders across the business

Excellent communication and presentation skills to different stakeholder audiences