Summary
Machine learning/Data science internship to work with predictive modeling and uncertainty estimation in the context of molecular property prediction and cheminformatics.
About the Role
Duration: 6 months
Start: as soon as possible
Location: Campus Basel
Major accountabilities:
- Develop ML models for compound property predictions
- Implement, apply and benchmark uncertainty estimation methods for ML models
- Work in a multidisciplinary environment
- Present project outcomes to technical and non-technical audiences
Minimum Requirements:
- MSc in a quantitative field or life sciences, preferably with multidisciplinary background (cheminformatics, bioinformatics, biomedical data science)
- Strong understanding of statistics and experience with machine learning / deep learning
- Expert knowledge of Python
- Experience with reproducible data science tools and practices
- Excellent communication skills and ability to translate analytical concepts for diverse audience and stakeholders (English is our primary language)
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Desired:
- Previous research experience either in academia or industry
- Experience with uncertainty quantification
- Knowledge of explainable AI
Skills:
- Python
- Statistics, machine learning, deep learning, predictive modeling
Languages :
- English
Accessibility and accommodation:
Novartis is committed to working with and providing reasonable accommodation to all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to receive more detailed information about the essential functions of a position, please send an e-mail to diversity.inclusion_ch@novartis.com, and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
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Division
Biomedical Research
Business Unit
Pharma Research
Location
Switzerland
Site
Basel (City)
Company / Legal Entity
C028 (FCRS = CH028) Novartis Pharma AG
Functional Area
Others
Job Type
Full time
Employment Type
Early Career (Fixed Term)
Shift Work
No