AWS, Dask - Python library, Git, Google Cloud Platform (GCP), Java Programming, Mercurial, NoSQL, NumPy, OpenCV, Pandas, Python Programming, Scikit-learn, SciPy, SQL
Global drug development productivity is declining exponentially, with an overall failure to develop effective treatments for many increasingly prevalent complex diseases affecting millions of patients per year. We seek to solve this by combining cutting-edge machine learning techniques with recent advances in life sciences to drastically improve how drugs are discovered and developed.
This summer we are looking for highly motivated interns looking to work at the intersection of machine learning and life sciences. As an omics intern, you will play a key role in modeling the molecular omics phenotypes of cells with different genetic / chemical perturbations, environmental exposures, and genetic backgrounds. As molecular omics is one of the two major ways that insitro leverages to model disease phenotypes, your contribution will be critical for identifying genes and pathways that are relevant to diseases, validating and understanding the role of gene hits from statistical genetics studies, and aligning phenotypic models between in vivo and in vitro systems.
Insitro has a highly dynamic and collaborative culture in a custom-built open office in South San Francisco. You will work closely with machine learning engineers and scientists, biologists, chemists, microscopy experts, and automation engineers. You will be mentored by one of our senior researchers, who has significant experience in machine learning for molecular omics data. You will also attend our machine learning team meetings and will be exposed to a diverse set of novel technologies and machine learning concepts that tackle various biological questions.
Join us, and help make a difference to patients!
About You
Nice to Have
Intern Benefits
Intern Benefits
insitro is a data-driven drug discovery and development company using machine learning and data at scale to transform the way that drugs are discovered and developed for patients. insitro is developing predictive machine learning models to discover underlying biologic state based on human cohort data and in-house generated cellular data at scale. These predictive models can be brought to bear on key bottlenecks in pharmaceutical R&D.
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
4-6 year
South San Francisco, CA, USA
2-4 year