Postdoctoral Position – Cheminformatics Team
Simulations Plus in Lancaster, CA
- Collect/Extract biological data related to (but not limited to) absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of small drug-like molecules from public domain literature or databases as well as commercial databases.
- Curate the data sets by verifying chemical structures and experimental data.
- Develop novel methods for analyzing data.
- Build machine learning models to predict properties of molecules.
- Closely collaborate with other interdisciplinary project teams to develop solutions to satisfy their needs.
- Ph.D. in computational chemistry, medicinal chemistry, biostatistics, biomedical engineering, or related fields and must have outstanding computer skills.
- Extensive hands-on experience in cheminformatics (i.e. chemical descriptors, similarity, diversity, SAR analysis, properties, library enumeration, design and chemical transformations) is required, with proven track record of accomplishments is preferred.
- Experience in applying machine learning libraries (R and/or scikit-learn, KNIME)
- Excellent communication, reporting and team interaction skills, self-motivation, proactivity and the ability to work independently, required.
- Basic understanding of organic chemistry and experimental biology will be beneficial.
Preference will be given to candidates with a background in quantitative structure activity relationships (QSAR) models but those with skills in other computational disciplines are welcome to apply.
- Lancaster or San Francisco, CA. Alternate locations will be considered.