AWS, C++, Deep Learning, Google Cloud Platform (GCP), Java Programming, JAX framework, Keras software library, OpenCV, Python Programming, PyTorch, SQL
Key to insitro’s approach to rethinking drug development is leveraging disease models, genetics, and clinical datasets to link in vitro and cellular phenotypes with patient outcomes.
Imaging based high content phenotyping is at the heart of insitro’s efforts to characterize and quantify sophisticated patient datasets. Our goal is to use machine learning to characterize image content and patient state from clinical imaging modalities such as pathology images in clinical cohorts.
As a machine learning / computer vision researcher with an emphasis on clinical data, your focus will be to develop innovative ML approaches to analyze and integrate large-scale medical imaging datasets such as histopathology, MRI, and other clinical imaging modalities from randomized clinical trials, electronic health records/PACS, national biobanks, and other sources. You will also work with colleagues to integrate those data with associated clinical, genetic, or other variables. Via this collaborative effort, you will have the opportunity to contribute to developing models for understanding patient disease state and progression, predicting patient outcomes, and identifying therapeutic targets and developing drugs that have high efficacy and low toxicity.
Your work will involve the development and deployment of cutting edge methods in both classical computer vision and deep learning. The data we deal with will require addressing challenges such as distribution shift, such as hospital site variability in histology stain characteristics, data missingness, class imbalance, and small sample sizes, among other unique challenges. You will need to develop fit-for-purpose approaches that utilize methods such as self-supervised learning, multi-task learning, few-shot learning, and more. You will work in collaboration with the software engineering team to develop these methods as robust, reusable platform components that can be deployed on large-scale datasets in a portable way.
You will be joining a vibrant biotech startup that has long-term stability, due to significant funding, and is in a high growth phase. A lot can change in this early and exciting phase, providing many opportunities for significant impact. You will work closely with a very 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!
This role is preferably based in the San Francisco Bay Area or Boston, but we are open to discussing other locations in the United States and the United Kingdom.
About You
Nice to Have
Benefits at insitro
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
South San Francisco, CA, USA
4-6 year
South San Francisco, CA, USA
4-6 year
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
0-2 year
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
0-2 year
South San Francisco, CA, USA
6-8 year
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
0-2 year
South San Francisco, CA, USA
0-2 year
South San Francisco, CA, USA
6-8 year
South San Francisco, CA, USA
4-6 year
South San Francisco, CA, USA
4-6 year