
Computational Scientist (Contractor) - gRED, Regev Lab
ICONMA · South San Francisco, CA
Hiring signal
Actively hiring
Posted 2 days ago · still listed on the employer's own board · How we score
All reasons
In its favour
- Posted 2 days ago
- Still listed on the employer's own board
Our Client, a Biotech company, is looking for a Computational Scientist (Contractor) - gRED, Regev Lab for their South San Francisco, CA location.
Responsibilities
- Multimodal perturbation datasets are becoming increasingly large and available, and understanding which data contribute most to model performance is an increasingly important question.
- The Regev lab has generated a large multimodal perturbation dataset.
- The contractor will train and evaluate models on this data to characterise how different portions of the dataset contribute to model learning, and will evaluate model performance and model outputs against experimental data.
- Ownership of a clearly scoped, business-critical workstream with defined deliverables.
- Direct collaboration with the project lead and access to an established, documented analysis codebase and cluster compute.
- Work with some of the most talented people in the biotechnology industry.
Requirements
- PhD in a computational discipline, or equivalent research experience
- Preferred majors: Computational Biology, Computational Sciences, Statistics or Machine Learning
- Required skills:
- Training and evaluating deep learning models in PyTorch, including designing and executing controlled train/test split experiments on a SLURM cluster.
- Strong applied statistics
- Proficient scientific Python (numpy, pandas, scanpy/anndata) and reproducible, documented analysis practice.
- Preferred Qualifications:
- Experience with single-cell transcriptomics
- Experience with analysis of CRISPR perturbation screens (perturb-seq or similar).
- Familiarity with representation learning
- Familiarity with image analysis
Why Should You Apply?
- Health Benefits
- Referral Program
- Excellent growth and advancement opportunities
Skills
- Machine Learning
- Deep Learning
- PyTorch
- Slurm
- Python
- NumPy
- Pandas
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