Principal ML Scientist – Predictive Toxicology
Tasks
- Apply federated learning for collaborative model development
- Build and optimize machine learning models for molecular AI
- Collaborate with customers on evaluation adoption and roadmap
- Define modeling approaches and data strategies
- Develop scalable solutions for safety and efficacy decisions
- Integrate multi omics and screening workflows
- Lead scientific strategy for predictive toxicology
- Mentor scientists and build scientific capabilities
- Translate scientific challenges into practical AI solutions
Perks/Benefits
- Co-working stipend
- Fully remote-first
- Generous holiday allowance
- Learning and professional development budget
- Mental health support
- Office days at European locations
- Wellbeing budget
- Work from home budget
Skills/Tech-stack
Cheminformatics | Computational Biology | Cytotoxicity | DILI | Data Privacy | Deep learning | Federated Learning | Genomics | Genotoxicity | Graph Neural Networks | High Throughput | High Throughput Screening | High-content imaging | Image Based Screening | Machine Learning | Molecular AI | Multi-Omics | Neural Networks | Privacy-preserving | Privacy-preserving machine learning | RNA-seq | Transformer Models
Education
Roles
ML Scientist | Principal | Principal ML Scientist | Scientist
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