Deep Learning Scientist in Genomics & Computational Biology

Rose International; South San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Rose International is seeking a highly qualified computational biology scientist to train and evaluate deep learning models on large multimodal perturbation datasets, using PyTorch on a SLURM cluster.

You will apply strong statistics and reproducible Python data analysis (numpy, pandas, scanpy/anndata) to characterize data contributions to model learning and collaborate with the Regev lab to align model outputs with experimental results.

Qualifications

• PhD in a computational discipline (computational biology, computational sciences, statistics or ML)
• Experience training deep learning models in PyTorch and evaluating with controlled train/test splits
• Proficiency in Python for data analysis (numpy, pandas, scanpy/anndata) with reproducible pipelines

Responsibilities

• Train and evaluate models on large multimodal perturbation datasets to understand data contributions to model performance
• Evaluate model outputs against experimental data from published datasets (Regev lab)
• Collaborate with researchers to interpret results and ensure reproducibility

Skills

PyTorch deep learning

Applied statistics

Python data analysis (numpy, pandas,/)

reproducible research

Education

PhD in computational discipline / computational biology / computational sciences / statistics / machine learning

Tools

SLURM cluster

Job description

Rose International is seeking a highly qualified computational biology scientist to train and evaluate deep learning models on large multimodal perturbation datasets, using PyTorch on a SLURM cluster.

You will apply strong statistics and reproducible Python data analysis (numpy, pandas, scanpy/anndata) to characterize data contributions to model learning and collaborate with the Regev lab to align model outputs with experimental results.