Machine Learning Researcher

PostEra is building an AI-first biotech. We use Proton, our AI platform for medicinal chemistry, to accelerate the discovery of new medicines for patients. PostEra is advancing an internal pipeline focused on Women's Health and Fertility, and has used Proton to nominate multiple clinical candidates across PMOS and Fertility. PostEra also advances small molecule programs through partnerships with pharma. We've closed over $1B in AI partnerships including 4 multi-year agreements with Pfizer and Amgen. PostEra is also leading an antiviral drug discovery center for pandemic preparedness, funded by one of the largest grants in NIH history. 

PostEra's Organizational Structure

• We believe time spent navigating complex hierarchies in organizations is better invested in the pursuit of novel technology and scientific discoveries. As such, our organizational structure is intentionally minimalist. 

• We promote a culture where individual achievement is celebrated through proportional compensation and internal recognition, including meaningful promotions.

• Ultimately, our collective focus is delivering cures to patients, which we believe needs a huge amount of cross-disciplinary collaboration, so we've fitted our organizational structure to serve that end.

Role Overview

In this role, you will develop the agentic research vertical at PostEra, using agentic systems to automate the development of mechanistic models for biochemical and physiological processes, and analyse biological data for target validation. You will interact closely with chemists and biologists to use these models to drive drug discovery decisions. 

You will also develop machine learning methods that can rapidly adapt to new drug discovery problems from limited labeled data. A particular focus is molecular and tabular in-context learning and building foundation models from PostEra’s proprietary multimodal data. You will build models that use the context of drug discovery effectively, determine which prior examples and tasks are relevant, quantify when transfer is helpful or harmful, and provide reliable predictions under distribution shift. 

You will help drive the full research loop: defining tasks, constructing datasets and evaluation episodes, developing strong baselines, training and scaling models, performing rigorous ablations, and translating successful methods into capabilities used by PostEra’s scientists. Prior drug discovery experience is not required, but you should be motivated to learn the domain and work closely with medicinal chemists, computational chemists, and other scientists.