Machine learning lies at the core of insitro’s approach to rethinking drug discovery and development. As a member of our machine learning-enabled drug discovery team you will bridge our machine learning and medicinal chemistry teams, working closely with engineers and scientists in these fields to create, organize and analyze large scale datasets relating molecular structure to biological and drug property data. You will be a member of cross-functional teams, comprising machine learning engineers, life scientists, bioengineers, automation engineers and data scientists, bringing machine learning to bear on the challenges of molecular target discovery and drug design. You will demonstrate world-class research skills and experience in developing and using cutting-edge cheminformatics and computational chemistry methods, as well as strong interpersonal skills, an ability to influence multidisciplinary teams, a strong collaborative work ethic, ability to adapt to changing needs, and the capacity to multitask to meet key goals. Strong communication and presentation skills are essential to success in this position.
Specifically, you will:
- Develop methods for data mining and statistical analysis of large datasets, such as external chemical and protein-structure databases, and large internally-generated structure-property datasets.
- Develop methods for retrieving and archiving data on molecular structures and molecular interactions for use in the generation of machine learning models.
- Identify chemical property classifications and trends from such databases using mathematical techniques, in order to gain insights supporting development of machine learning models.
- Enhance insitro’s current suite of informatics tools to advance our cheminformatics and drug design environment, and integrate them with our machine learning platform.
- Identify and evaluate new modeling and informatics technology and software applications from commercial sources or through external collaborations.
- Contribute to the design of molecule screening collections for target based, virtual, DEL, and phenotypic screening, across a range of modalities.
- Design and develop novel tools for analyses and visualization of chemical, biological, and structural data
You will be joining the founding team of a biotech startup that has long-term stability due to significant funding, but yet is very much in formation. Much can change in this early and exciting phase, providing many opportunities for significant impact. You will work closely with an exceptionally talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!
- Ph.D. in computational chemistry or equivalent experience
- An outstanding scientific track record in your area of expertise
- Good working knowledge of medicinal and organic chemistry, DMPK, and preclinical toxicology principles
- Experience in CADD: structure and/or ligand-based drug design, QSAR, and pharmacophore modeling
- Good working knowledge of existing application containment systems (Docker etc), molecular software (RDKit, Schrodinger suite), and pipeline managers ( Knime, Airflow, Nextflow etc)
- A demonstrated deep understanding of 3D protein-ligand interactions applied to molecular design concepts
- Experience in applying cheminformatics approaches to solving problems in data mining, implementing new tools, and generating automated workflows
- Excellent oral and written communication skills
- Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions in a fast-paced, goal-oriented team environment
- Passion for making a difference in the world
Nice to Have
- 5+ years of relevant experience in the pharmaceutical or biotech industry
- Experience in molecular docking, molecular simulations, virtual screening, Free-energy perturbation methods, and PK/PD data analysis
- Experience in machine learning and bioinformatics
- Experience with biological data (DNA sequences, RNAseq, proteomics, microscopy images, etc.)
- A demonstrated expertise in scientific programming (e.g., Python, Java, C++, SVL) with practical application of these skills is a strong plus
- Familiarity with cloud computing services (AWS)
insitro is a data-driven drug discovery and development company using machine learning and data generation at scale to transform the way that drugs are discovered and delivered to patients. insitro’s approach focuses on the development of predictive machine learning models to be brought to bear on key bottlenecks in pharmaceutical R&D. The company has established enabling collaborations with Gilead in NASH and Bristol Myers Squibb in ALS. insitro is located in South San Francisco, CA and has been supported by top tech, biotech, and crossover investors since formation in 2018. For more information on insitro, please visit the company’s website at www.insitro.com.