Computational Scientist
South San Francisco, CA
Computational Scientist
Develop, train, and evaluate deep learning models on large-scale multimodal perturbation datasets; full-time, 40 hours per week, 12-month contract with possible extension. Requires a PhD or equivalent research experience, PyTorch, controlled train/test experiments, SLURM HPC, and scientific Python.
Job Title: Computational Scientist
Location: 1 DNA Way, South San Francisco, CA 94080
Pay Rate: $36.97 - $53.97/hour + Benefits
Benefits: Weekly Pay, Medical, Dental, and Vision Insurance
Contract Duration: 12 Months (Potential for Extension)
Work Schedule: Full-Time, 40 Hours per Week
Position Overview
We are seeking a skilled Computational Scientist to support the Regev Lab in analyzing large-scale multimodal perturbation datasets. The primary focus of this role is to develop, train, and evaluate deep learning models to understand how different components of multimodal datasets contribute to model performance and learning outcomes.
The selected candidate will work with large-scale experimental datasets, assess model outputs against experimental findings, and generate insights to improve model performance and reliability.
Key Responsibilities
Required Education
Required Technical Skills
Preferred Qualifications
Contract Highlights
Location: 1 DNA Way, South San Francisco, CA 94080
Pay Rate: $36.97 - $53.97/hour + Benefits
Benefits: Weekly Pay, Medical, Dental, and Vision Insurance
Contract Duration: 12 Months (Potential for Extension)
Work Schedule: Full-Time, 40 Hours per Week
Position Overview
We are seeking a skilled Computational Scientist to support the Regev Lab in analyzing large-scale multimodal perturbation datasets. The primary focus of this role is to develop, train, and evaluate deep learning models to understand how different components of multimodal datasets contribute to model performance and learning outcomes.
The selected candidate will work with large-scale experimental datasets, assess model outputs against experimental findings, and generate insights to improve model performance and reliability.
Key Responsibilities
- Train, develop, and evaluate deep learning models using large-scale multimodal perturbation datasets.
- Analyze how different subsets and components of datasets contribute to model learning and overall performance.
- Design and execute controlled training and testing experiments.
- Evaluate model predictions and outputs against experimental data.
- Perform statistical analysis to assess model performance and validate findings.
- Work with existing analysis codebases and cluster computing infrastructure.
- Maintain reproducible, well-documented, and structured analytical workflows.
- Collaborate directly with the project lead and research team to deliver defined project milestones.
Required Education
- PhD in a computational discipline or equivalent research experience.
- Preferred academic backgrounds include:
- Computational Biology
- Computational Sciences
- Statistics
- Machine Learning
Required Technical Skills
- Hands-on experience training and evaluating deep learning models using PyTorch.
- Experience designing and executing controlled train/test split experiments.
- Familiarity with SLURM-based high-performance computing (HPC) clusters.
- Strong applied statistics and analytical skills.
- Proficiency in scientific Python libraries, including:
- NumPy
- Pandas
- Scanpy
- AnnData
- Experience developing reproducible, well-documented scientific analysis workflows.
Preferred Qualifications
- Experience working with single-cell transcriptomics data.
- Experience analyzing CRISPR perturbation screens, including Perturb-seq or similar technologies.
- Familiarity with representation learning techniques.
- Experience or familiarity with image analysis.
Contract Highlights
- Full-time engagement of 40 hours per week.
- Initial 12-month contract.
- Ownership of a clearly defined, business-critical research workstream with measurable deliverables.
- Direct collaboration with the project lead.
- Access to an established, documented analysis codebase and cluster computing resources.
- Opportunity to collaborate with leading researchers and talented professionals in the biotechnology industry.
At Tailored Management, we help people get jobs and take pride in their work, so we better take pride in ours too. Not every company has the opportunity to meaningfully and directly impact individuals in a way that makes their lives tangibly better. To better support our employees, we offer a wide variety of benefit options to support you. We offer:
- Medical Coverage – HDHP, PPO, and Surest plan options
- Minimum Essential Coverage (MEC)
- Dental Insurance
- Vision Insurance
- Short-Term Disability (STD)
- Long-Term Disability (LTD)
- Life & AD&D Insurance
- Critical Illness Insurance
- Accident Insurance
- Employee Assistance Program (EAP)