Computational Scientist

Sharp Decisions; South San Francisco (CA); Vor Ort; USD 120.000 - 180.000; Vollzeit

Zusammenfassung

Sharp Decisions seeks a Computational Scientist (Contractor) to join the gRED Regev Lab in South San Francisco, on-site for a 12-month term. You will train and evaluate deep learning models on a multimodal perturbation dataset, assess data contributions to model performance, and compare results to experimental data.

You will work with an established codebase and a SLURM cluster. The ideal candidate holds a PhD in a computational field or equivalent research experience, is proficient in PyTorch,

Qualifikationen

• PhD in a computational discipline or equivalent research experience.
• Experience training deep learning models with PyTorch on SLURM clusters.
• Strong applied statistics and proficiency with Python libraries (NumPy, Pandas, Scanpy, AnnData).
• Experience with reproducible and well-documented analysis practices.

Aufgaben

• Train and evaluate models on multimodal perturbation datasets.
• Characterize how data portions affect model learning and performance against experimental data.
• Collaborate with project lead and access established analysis codebase and cluster compute.
• Deliver clearly scoped workstream with defined deliverables.

Kenntnisse

PyTorch

SLURM cluster

Applied statistics

NumPy

Pandas

Scanpy

AnnData

Ausbildung

PhD in computational discipline or equivalent research experience

Jobbeschreibung

Computational Scientist (Contractor) - gRED, Regev LabDescription

This contract position is located in South San Francisco, CA (100% Onsite).

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. The contractor will also evaluate model performance and model outputs against experimental data.

Contract Highlights

• Full-time position, 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.
• Opportunity to 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
• Machine Learning

Required Skills

• Experience training and evaluating deep learning models using PyTorch, including designing and executing controlled train/test split experiments on a SLURM cluster.
• Strong applied statistics skills.
• Proficiency in scientific Python libraries, including NumPy, Pandas, Scanpy, and AnnData.
• Experience with reproducible and well-documented analysis practices.

Preferred Qualifications

• Experience with single-cell transcriptomics.
• Experience analyzing CRISPR perturbation screens (Perturb-seq or similar).
• Familiarity with representation learning.
• Familiarity with image analysis.