✨ About The Role
- The role involves designing and implementing software that utilizes informatics, machine learning, and computational chemistry to address drug discovery needs.
- The successful candidate will contribute to research leveraging physics-based simulation, deep learning, and knowledge graphs for drug discovery applications.
- Collaboration with an interdisciplinary team of scientists is essential to identify hits and optimize leads in ongoing drug discovery programs.
- The position requires leveraging Bayesian optimization and active learning to enhance experimental designs and make data-driven decisions.
- The candidate will also be responsible for translating research insights into maintainable software systems and contributing to the scientific community through publications and presentations.
âš¡ Requirements
- A PhD in chemistry, biology, computer science, or a related discipline is essential for this role.
- The ideal candidate will have 1-5 years of relevant experience in informatics, machine learning, and computational chemistry applied to drug discovery.
- Experience with cheminformatics and bioinformatics methods is crucial, including techniques like similarity searching and sequence alignment.
- Proficiency in common Python toolkits for scientific computing and machine learning is required, demonstrating technical skills in tools such as NumPy, Pandas, and PyTorch.
- A strong interest in solving scientific problems in chemistry and biology through computational methods is necessary for success in this position.