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Insilico Medicine Logo

Machine Learning Researcher

316a794

Remote

1 day ago

Insilico Medicine

Hong Kong, Hong Kong

Unknown / Non-Applicable

Company - Private


Job Description

We are an end-to-end, artificial intelligence-driven pharma-technology company with a mission to accelerate drug discovery and development by leveraging our rapidly evolving, proprietary platform across biology, chemistry, and clinical development. Our Pharma.AI platform has the potential to rapidly bring novel breakthrough medicines to patients while decreasing costs and increasing the probabilities of success.
Insilico Medicine is seeking a Machine Learning Researcher for molecular predictive models in Chemistry & Biology:

The candidate will
  • Research new state-of-the-art predictive models
  • Prototype existing or new ML predictive approaches
  • Propose various solutions to improve the predictive performance of the models and the predictive pipeline
  • Make experiments (i.e., build predictive models) with the provided dataset

Requirements

  • Strong background in ML
  • At least two years of experience in Python
  • An ability to test hypotheses and prototype in a short time
  • An ability to absorb a large amount of information from various sources
  • Motivation to learn new things and apply creative solutions to improve drug discovery
  • Proven track of scientific publications in machine learning for the last 1 year
  • Experience in Numpy, Pandas, Pytorch, Scikit-Learn, Git, Linux, Bas

Desirable skills
  • Background in DL
  • Feature engineering
  • Successful experience in machine learning competitions
  • Be experienced in RDKit, CGRTools, ChemAxon
  • Knowledge of Cheminformatics will be an advantage

Terms and conditions
  • Fixed salary + annual bonus
  • Voluntary health insurance program and language courses (English and Chinese) after the probation period
  • Reimbursement of training programs, participation in conferences and webinars, course certificates
  • Friendly team and warm environment
  • Flexible working schedule

Please send your CV to [email protected]


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