Calico is seeking to advance the state-of-the-art in modelling binding affinity through machine learning based molecule design
Requirements
Experience applying machine learning to solve challenging problems, and with modern machine learning techniques
Knowledge of Python and deep learning frameworks (such as PyTorch, TensorFlow, JAX)
Strong analytical and quantitative problem solving skills
Experience in molecule design, cheminformatics, ranking or geometric deep learning
Responsibilities
Gain expertise in state-of-the-art research in machine learning based molecule design
Implement novel ideas for ranking the designs
Develop benchmarks to validate models and compare performance to existing internal and public methods
Communicate results through presentation and/or publication
Other
Currently pursuing a MS or PhD degree, in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, Statistics, Applied Mathematics, Physics or related field
Detail-oriented and organized
Strong teamwork and communication skills
Self-motivated with a “can-do” attitude
Able to work in-person at our offices in South San Francisco
