
Turbine provides the world's first cell simulation platform, enabling scientists to test hypotheses and make data-driven R&D decisions. Their platform, Simulated Cell™, augments pipelines by simulating payloads for Antibody-Drug Conjugates (ADCs), identifying optimal patient populations for clinical trials, and unlocking the commercial potential of drug resistance inhibitors. Turbine's approach uses mechanistic hypotheses, leading to a 50% higher likelihood of validation and a 2x faster timeline from scientific question to validation. They can engineer any sample to simulate and test perturbations, exploring over 50 million experiments per day. Key benefits include faster identification of novel targets, causal hypotheses for improved translatability, and biomarker-driven target identification. Turbine has partnered with major pharmaceutical companies, demonstrating impact across discovery, preclinical, and development stages.

Turbine provides the world's first cell simulation platform, enabling scientists to test hypotheses and make data-driven R&D decisions. Their platform, Simulated Cell™, augments pipelines by simulating payloads for Antibody-Drug Conjugates (ADCs), identifying optimal patient populations for clinical trials, and unlocking the commercial potential of drug resistance inhibitors. Turbine's approach uses mechanistic hypotheses, leading to a 50% higher likelihood of validation and a 2x faster timeline from scientific question to validation. They can engineer any sample to simulate and test perturbations, exploring over 50 million experiments per day. Key benefits include faster identification of novel targets, causal hypotheses for improved translatability, and biomarker-driven target identification. Turbine has partnered with major pharmaceutical companies, demonstrating impact across discovery, preclinical, and development stages.
Join our team as a Machine Learning Engineer and help us understand and tackle cancer!
As a Machine Learning Engineer, you'll be an integral part of our applied research team, focusing on modeling the behavior of cancer cells. Our research teams are dedicated to creating and training novel cancer cell models, allowing us to simulate hundreds of millions of samples for real-world applications. In a mixed team of ML scientists, engineers and bioinformaticians, you'll have the opportunity to work closely with people who tackle hard, unsolved machine learning problems.
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