🌟 We're Hiring: Machine Learning and Computational Chemistry Scientist! 🌟
We are seeking to hire a Machine Learning and Computational Chemistry Scientist in
South San Francisco, CA.
📍 Location: South San Francisco, United States
⏰ Work Mode: Work From Office
💼 Role: Machine Learning and Computational Chemistry Scientist
Pay Scale: $72, 529 – $174, 604 (Dependent on Experience)
What You'll Do:
· Implement machine learning and computational chemistry-based methods to enhance
mass-spectrometry workflows, focusing on small molecule drug discovery, ensuring high
accuracy and efficiency in analytical processes.
· Closely collaborate with other scientists and researchers within and outside MLDD to
identify platform development and automation opportunities for analytical workflows that
facilitate drug discovery research.
· Build and scale the mass-spectrometry and analytical chemistry platform by deploying novel
machine learning and computational algorithms in collaboration with experimental teams that
meet the research needs of the broader department and the Client Company's community.
· Contribute to and drive publications, present results at internal and external scientific
conferences, and help make code and workflows open source.
What we are looking for in a Machine Learning and Computational Chemistry Scientist:
· MS or PhD degree in the physical sciences (e.g. Chemistry, Physics, Chemical Engineering) or
quantitative field (e.g. Computer Science, Machine Learning) or equivalent industry research
experience.
· 3-5 years of applicable experience.
· Record of scientific excellence as evidenced by at least one publication in a scientific journal
or conference.
· Fluent in Python and experience with scientific software development for analytical
chemistry (e.g. RDKit, MS data suite including, but not limited to, Proteowizard, Sirius, GNPS,
XCMS, Asari)
· Demonstrated experience with modern Python frameworks for deep learning like PyTorch
Ready to revolutionize chemical research? 🚀 Apply now and let's innovate together!
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