Citrine Informatics is revolutionizing how raw materials and chemicals are produced by empowering companies to develop them faster and more sustainably. Working at Citrine offers the rare opportunity to collaborate with applied scientists at the leading edge of statistical learning theory and application.
Here are a few representative peer-reviewed publications describing research done at Citrine in support of the platform’s AI capabilities:
Assessing the Frontier: Active Learning, Model Accuracy, and Multi-objective Materials Discovery and Optimization (2019). at https://arxiv.org/abs/1911.03224 Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery (2018). at https://doi.org/10.1039/C8ME00012C Overcoming data scarcity with transfer learning. (2017). at https://arxiv.org/abs/1711.05099 High-Dimensional Materials and Process Optimization Using Data-Driven Experimental Design with Well-Calibrated Uncertainty Estimates. (2017). at https://doi.org/10.1007/s40192-017-0098-z
Learn more at: https://jobs.lever.co/citrineinformatics