Machine Learning Scientist
Tasks
- Analyze single-cell RNA-seq data
- Apply fine tune foundation models
- Build mechanistic interpretability methods
- Collaborate with interdisciplinary science teams
- Deploy models on cloud using MLOps
- Develop perturbation models for biological data
- Establish benchmarking and evaluation frameworks
- Run inference on generative models
Perks/Benefits
Skills/Tech-stack
AWS | Attention Mechanisms | CRISPR | Causal Inference | Causal Representation Learning | Cloud Computing | Deep learning | Diffusion Models | Foundation Models | GCP | Gene Regulatory Networks | Generative AI | Graph Neural Networks | MLOps | Machine Learning | Model Benchmarking | Multi-Omics | Multi-Omics Integration | Neural Networks | Omics integration | Perturb-seq | Perturbation modeling | Protein Interaction Networks | Protein Protein Interaction Networks | Protein protein interaction | RNA-seq | Representation Learning | Single-cell | Single-cell RNA-seq | Transformer | Variational Autoencoder
Education
Regions
Countries
States
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