Machine Learning Cheminformatics Engineer - Drug Discovery

October 26

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Description

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

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.

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 • More.