The Waters Informatics department is looking to solve the problem of creating scientific mechanistic and machine learning models to contribute to the next generation of innovations in intelligent instrumentation, specifically in the areas of chromatography and mass spectrometry systems.
Requirements
- Experience in model development using Python for machine learning, statistical, and mechanistic models
- Robust object-oriented and/or functional programming skills in languages including C, and Python. C++ desirable.
- Comfortable with Git version control, and either BASH or command prompt
- Proficiency with AWS Lambda, S3, EC2, or Redshift desirable
- Experience with mechanistic modeling and machine learning
- Programming skills in languages including Python and C
Responsibilities
- Explore various scientific, statistical and machine learning approaches, explore data features, generate metrics, and evaluate results associated with collection and analysis of chromatographic and mass spectrometric data
- Assist subject matter experts (SMEs) in model evaluation and stakeholder presentations
- Use object-oriented programming and functional programming best practices to maintain codebases in python and C, and write unit tests
- Contribute to the preparation of technical reports, patent applications, and transferable protocols
- Contribute to the construction and maintenance of the AWS data pipeline
- Maintain up-to-date knowledge of relevant scientific literature
Other
- 5 or more years of practical experience in mechanistic modeling and machine learning
- S. or PhD in computer science, data science, or scientific field with a computational focus
- Able to communicate results using meaningful metrics and visualizations to managers and stakeholders and receive feedback.
- Diversity and inclusion are fundamental to our core values at Waters Corporation
- Waters is proud to be an equal opportunity workplace and is an affirmative action employer
