Principal Machine Learning Scientist (alle Gechlechter)
Tasks
- Accelerate drug discovery using internal and external AI capabilities
- Build virtual cell and patient models
- Collaborate with r d colleagues and external partners
- Communicate with stakeholders across biology chemistry data science and r d leadership
- Develop evaluate and apply machine learning models
- Integrate foundation models for protein RNA and single cell and spatial omics
- Lead initiatives for integrating ai into biomedical research
- Simulate cellular states and support in silico patient stratification
- Stay current on foundation models and virtual modeling and present findings
Perks/Benefits
- Coaching and mentoring
- Health checks
- Health seminars
- Hybrid work model
- Learning and development
- Onsite childcare
Skills/Tech-stack
Agentic AI | Bioinformatics | Cell analysis | Data integration | Deep learning | Digital Twins | Drug Discovery | Foundation Models | Generative Models | Language Models | Machine Learning | Multimodal Learning | Multimodal fusion | Multiomics integration | Network Analysis | Pandas | Protein Language Models | PyTorch | Python | RNA Language Models | Scikit-learn | Single Cell Analysis | Single-cell | Spatial omics
Education
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