Remote Machine Learning Cheminformatics Engineer

Summary

Join SandboxAQ's AI Simulation group and contribute to innovative drug discovery projects leveraging cheminformatics, machine learning, and computational chemistry. As a researcher, you will design and implement software, collaborate with an interdisciplinary team, and translate research to maintainable software systems.

Requirements

• PhD in chemistry, biology, computer science, or a related discipline
• 1-5 years of relevant experience including hands-on experience with informatics, machine learning, and computational chemistry applied to drug discovery in the private sector, like biotech or pharma
• Experience with cheminformatics and bioinformatics methods (e.g., similarity / substructure searching, reaction-based enumeration, sequence alignment, etc.)
• Experience with molecular property prediction and multi-objective optimization using machine learning and / or deep learning methods
• Experienced with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., scikit-learn, pytorch), and cheminformatics / bioinformatics (e.g., rdkit, openeye, biotite, biopython)
• Familiarity running simulations and training models on high-performance computing (GPU) environments for corporate R&D, innovation labs, or academic research
• An interest in solving scientific problems in chemistry and biology via computational and data-driven methods
• A drive to cooperate with colleagues to identify problems and communicate technical solutions in an accessible manner
• Hands-on mentality & comfortable with getting deep into the technical weeds of highly complex problems, and a track record of driving projects to completion

Responsibilities

• Design and implement software that leverages informatics, machine learning, and computational chemistry to address unmet needs in drug discovery
• Contribute to ongoing research leveraging physics-based simulation, deep learning, and knowledge graphs for drug discovery applications
• Work closely with an interdisciplinary team of scientists to identify hits and optimize leads in ongoing drug discovery programs
• Leverage Bayesian optimization and active learning to improve experimental designs and make data-driven decisions
• Collaborate with computational chemistry experts and cross-functional teams to rapidly prototype and scale cutting-edge, impactful drug design solutions
• Translate research and applications to maintainable software systems
• Contribute to the scientific community by writing patents / journal articles and presenting at conferences
• Translate insights from statistics, multimodal data analysis, and ML to actionable and testable drug discovery hypothesis
• This is an opportunity to directly contribute to the discovery of novel innovative medicines by applying computational chemistry techniques on teams with experienced multidisciplinary drug hunters

Benefits

• Competitive salaries
• Stock options depending on employment type
• Generous learning opportunities
• Medical/dental/vision
• Family planning/fertility
• PTO (summer and winter breaks)
• Financial wellness resources
• 401(k) plans