Computational Biologist

Title: Computational Biologist (Contract)
Department: Genentech Research and Early Development - CBT-OMNI
Start date: ASAP
Length of assignment: Through Dec 19, 2025
Location: Onsite in SSF, CA preferred. Remote OK, but must be available during PST.
Preferred Disciplines: Computational Biology, Computer Science, Statistics, Bioinformatics, Bioengineering, or a related quantitative field
Job Description: The mission of the CBT-OMNI Department is to facilitate drug discovery and development by understanding the biological mechanisms of diseases through the integration of multi-omics data derived from wet-lab experiments and cutting-edge computational and statistical methods.
Responsibilities: Project Title: Developing computational and statistical methods to detect disease-associated cell-cell interactions
Understanding disease-associated cell-cell interactions provides mechanistic disease insights and facilitates target discovery. In this project, we aim to develop a tool to detect disease-associated cell-cell interactions testing for differential correlation of cell abundance. The successful candidate will contribute to the derivation, implementation, and evaluation of computational methods/tools to detect disease-associated cell-cell interactions using single-cell data. The successful candidate will then apply the tool to analyze large-scale single-cell disease atlas data to identify disease-associated cell-cell interactions and extract mechanistic disease insights.
Specifically, the day-to-day activities will include:
* Deriving and implementing statistical methods to identify disease-associated cell-cell interactions
* Performing numerical simulations to evaluate the performance of the computational tool
* Applying the tool to analyze single-cell disease atlas data to identify disease-associated cell-cell interactions
* Integrating results from different analyses to interpret disease-associated cell-cell interactions and extract mechanistic disease insights
* Presenting project progress and results at team and departmental meetings
The deliverables expected by the end of the contract will include: * Software implementing the methods to identify disease-associated cell-cell interactions * Written documents describing derivations of the methods, benchmarks of the methods, and application of the methods * Presentation slides deck summarizing the work performed during the contract period
Qualifi cations:
* M.S. or Ph.D. in Computational Biology, Computer Science, Statistics, Bioinformatics, Bioengineering, or a related quantitative field
* Proven experience in analyzing single-cell RNA-seq data
* Experience in developing statistical and computational methods/tools
* Proficiency in Python, R, Unix, Git, and using HPC
* Experience with bioinformatics analysis tools such as Scanpy and Seurat is desired.
* Experience in analyzing spatial transcriptomics data is a plus.