Machine Learning Informatics Engineer

Summary

Join SandboxAQ's AI Simulation group as a researcher to drive innovative drug discovery projects. Leverage your expertise in informatics, machine learning, and computational chemistry to design and implement software solutions. Collaborate with a multidisciplinary team of scientists, leveraging Bayesian optimization and active learning. Contribute to ongoing research using physics-based simulation and deep learning. Translate research into maintainable software and contribute to the scientific community through publications and presentations. This role offers the opportunity to directly contribute to the discovery of novel medicines.

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
• Located in EMEA

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

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