Senior Expert II, Data Science, Modeling & Simulation
$102,200–$189,800 year
HybridBasel, Basel-City, Switzerland
Job Summary
Contribute to drug discovery and lead optimization programs by providing scientific and strategic input on compound progression and in vivo study prioritization using dry- and wet-lab data. Master in silico models and in-house tools to accelerate decision-making, while applying data mining to understand relationships between structure and molecular properties for small molecules, peptides, and RNAs. Create custom, project-specific in silico models and data strategies, then increase the impact of M&S Data Science through clear communications with internal and external audiences. Stay current on AI/ML developments applied to ADME and PK/PD to enhance these methods.
Required Qualifications
- Advanced degree in life sciences with multidisciplinary background (cheminformatics, bioinformatics, biomedical engineering, AI/ML in drug discovery or life sciences, data science, computational biology, computational chemistry or related field)
- PhD with a minimum of 3-4 years or MSc with 7-8 plus years of relevant work experience with deep knowledge on drug discovery and development processes
- Experience in the application of (reproducible) data science methods, tools and practices to drug discovery
- Strong understanding of statistics, machine learning and deep learning
- Demonstrated knowledge of data visualization and exploratory analysis
- Solid skills in programming languages, i.e. Python and R, including software development practices such as version control, testing, documentation, etc.
- Knowledge of machine learning/deep learning libraries such as scikit-learn, keras or pytorch
- Excellent communication skills and ability to translate analytical concepts for diverse audience and stakeholders (English is our primary language)
Desired Qualifications
- Expertise with discovery-stage PK modeling for small molecule compounds (e.g., relating ADME properties to in vivo PK; scaling of preclinical PK to human) is a plus
- Experience with generative algorithms and explainable AI
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