Remote Machine Learning Cheminformatics Engineer
at SandboxAQ

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SandboxAQ

πŸ’΅ $142k-$198k
πŸ“Remote - United States, Canada

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

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