Computational Scientist

Motion Recruitment; South San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Motion Recruitment in South San Francisco is seeking a Computational Scientist to work on a large multimodal perturbation dataset. The contractor will train and evaluate deep learning models, and assess how different data portions influence model learning against experimental results.

The role requires a PhD in a computational field, strong statistics, and proficiency with Python and PyTorch, with access to established codebase and SLURM compute resources.

Qualifications

• PhD or equivalent research experience in a computational field.
• Expertise in training and evaluating DL models with PyTorch on controlled splits.
• Strong applied statistics and reproducible data analysis practice.

Responsibilities

• Train and evaluate models on multimodal perturbation data to assess data contributions to learning.
• Evaluate model outputs against experimental data to validate findings.
• Collaborate with the project lead and maintain the analysis codebase and cluster compute.

Skills

DL model training

Applied statistics

Scientific Python

Education

PhD in computational discipline

Preferred: Computational Biology / Computational Sciences / Statistics / ML

Tools

PyTorch

Python (NumPy/Pandas/Scanpy)

Job description

Job Title

Computational Scientist

Job Location

South San Francisco, California, 94080 (Onsite)

Contract Duration

12 months with possible extension

Key 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 characterize how different portions of the dataset contribute to model learning, and will evaluate model performance and model outputs against experimental data.

Contract Highlights

Full time, 40 hours per week, for an initial term of 12-months.

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.

Required Education

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