Genentech is at the forefront of advancing spatial omics capabilities within their Research ... data (transcriptomics/proteomics) to uncover spatial niches and cell-cell interactions. • ...
Genentech is at the forefront of advancing spatial omics capabilities within their Research ... data (transcriptomics/proteomics) to uncover spatial niches and cell-cell interactions. • ...
Senior Scientist, Spatial Multi-Omics Biology for Early Drug Discovery
San Diego, CA · On-site
$97.10K - $132.70K/yr
... multi-omics technologies to join the Protein Homeostasis Department at Bristol Myers Squibb (BMS ... Generate high-quality spatial transcriptomics datasets from FFPE, fresh-frozen, preclinical ...
Senior Scientist, Spatial Multi-Omics Biology for Early Drug Discovery
San Diego, CA · On-site
$97.10K - $132.70K/yr
... multi-omics technologies to join the Protein Homeostasis Department at Bristol Myers Squibb (BMS ... Generate high-quality spatial transcriptomics datasets from FFPE, fresh-frozen, preclinical ...
Computational Scientist 3, Spatial Omics & Computational Pathology
South San Francisco, CA · On-site
$129.20K - $240K/yr
DPIA-SO (Digital Pathology Image Analysis-Spatial Omics) is a specialized team within Research ... Demonstrated experience applying machine learning to single-cell spatial transcriptomics and/or ...
Computational Scientist 3, Spatial Omics & Computational Pathology
South San Francisco, CA · On-site
$129.20K - $240K/yr
DPIA-SO (Digital Pathology Image Analysis-Spatial Omics) is a specialized team within Research ... Demonstrated experience applying machine learning to single-cell spatial transcriptomics and/or ...
Computational Scientist 3, Spatial Omics & Computational Pathology
South San Francisco, CA · On-site
$129.20K - $240K/yr
DPIA-SO (Digital Pathology Image Analysis-Spatial Omics) is a specialized team within Research ... Demonstrated experience applying machine learning to single-cell spatial transcriptomics and/or ...
Computational Scientist 3, Spatial Omics & Computational Pathology
South San Francisco, CA · On-site
$129.20K - $240K/yr
DPIA-SO (Digital Pathology Image Analysis-Spatial Omics) is a specialized team within Research ... Demonstrated experience applying machine learning to single-cell spatial transcriptomics and/or ...
Deep expertise in single-cell and spatial transcriptomics analysis, including scRNA-seq and related high-dimensional omics datasets * Strong experience analyzing functional genomics and ...
Deep expertise in single-cell and spatial transcriptomics analysis, including scRNA-seq and related high-dimensional omics datasets * Strong experience analyzing functional genomics and ...
Biomedical Specialist - Applied Genomics, Computation & Translational Core
West Hollywood, CA · On-site
$75.52K - $117.06K/yr
We specialize in single cell omics and spatial transcriptomics via the 10x Genomics, Parse Biosciences, Mission Bio, and NanoString platforms. Our R&D team offers sample preparation for single cell ...
Biomedical Specialist - Applied Genomics, Computation & Translational Core
West Hollywood, CA · On-site
$75.52K - $117.06K/yr
We specialize in single cell omics and spatial transcriptomics via the 10x Genomics, Parse Biosciences, Mission Bio, and NanoString platforms. Our R&D team offers sample preparation for single cell ...
Deep expertise in single-cell and spatial transcriptomics analysis, including scRNA-seq and related high-dimensional omics datasets * Strong experience analyzing functional genomics and ...
Deep expertise in single-cell and spatial transcriptomics analysis, including scRNA-seq and related high-dimensional omics datasets * Strong experience analyzing functional genomics and ...
Computational Biologist
San Francisco, CA · On-site
$125K - $185K/yr
Analyze multi-modal omics data. Apply cutting-edge techniques, including scRNAseq, spatial transcriptomics, and long-read sequencing, to derive meaningful insights from complex patient datasets.
Computational Biologist
San Francisco, CA · On-site
$125K - $185K/yr
Analyze multi-modal omics data. Apply cutting-edge techniques, including scRNAseq, spatial transcriptomics, and long-read sequencing, to derive meaningful insights from complex patient datasets.
We specialize in single cell omics and spatial transcriptomics via the 10x Genomics, Parse Biosciences, Mission Bio, and NanoString platforms. Our R&D team offers sample preparation for single cell ...
We specialize in single cell omics and spatial transcriptomics via the 10x Genomics, Parse Biosciences, Mission Bio, and NanoString platforms. Our R&D team offers sample preparation for single cell ...
Postdoctoral Fellow, Computational Biology & Medicine/Neuroscience
South San Francisco, CA · On-site
$110K - $120K/yr
Experience with bulk and/or single-cell omics data analysis (e.g. bulk genomics, transcriptomics, proteomics, single-cell RNA-seq, Perturb-seq, spatial transcriptomics ) * Proven ability to bridge ...
Postdoctoral Fellow, Computational Biology & Medicine/Neuroscience
South San Francisco, CA · On-site
$110K - $120K/yr
Experience with bulk and/or single-cell omics data analysis (e.g. bulk genomics, transcriptomics, proteomics, single-cell RNA-seq, Perturb-seq, spatial transcriptomics ) * Proven ability to bridge ...
Postdoctoral Fellow, Computational Biology & Medicine/Neuroscience
South San Francisco, CA · On-site
$110K - $120K/yr
Experience with bulk and/or single-cell omics data analysis (e.g. bulk genomics, transcriptomics, proteomics, single-cell RNA-seq, Perturb-seq, spatial transcriptomics ) * Proven ability to bridge ...
Postdoctoral Fellow, Computational Biology & Medicine/Neuroscience
South San Francisco, CA · On-site
$110K - $120K/yr
Experience with bulk and/or single-cell omics data analysis (e.g. bulk genomics, transcriptomics, proteomics, single-cell RNA-seq, Perturb-seq, spatial transcriptomics ) * Proven ability to bridge ...
... join our Spatial Omics team. The successful candidate will be responsible for planning, executing, and reporting complex Spatial Proteomics and/or Spatial Transcriptomics experiments. Key ...
... join our Spatial Omics team. The successful candidate will be responsible for planning, executing, and reporting complex Spatial Proteomics and/or Spatial Transcriptomics experiments. Key ...
Director, Computational Biology
Carlsbad, CA · On-site +1
Experience in multi-omics analyses and integration (including RNA-seq, ATAC-seq - bulk, single cell - spatial transcriptomics, proteomics, metabolomics, ChIP-seq and similar, long read RNA-seq, small ...
Director, Computational Biology
Carlsbad, CA · On-site +1
Experience in multi-omics analyses and integration (including RNA-seq, ATAC-seq - bulk, single cell - spatial transcriptomics, proteomics, metabolomics, ChIP-seq and similar, long read RNA-seq, small ...
Director, Computational Biology
Carlsbad, CA · On-site +1
Experience in multi-omics analyses and integration (including RNA-seq, ATAC-seq - bulk, single cell - spatial transcriptomics, proteomics, metabolomics, ChIP-seq and similar, long read RNA-seq, small ...
Director, Computational Biology
Carlsbad, CA · On-site +1
Experience in multi-omics analyses and integration (including RNA-seq, ATAC-seq - bulk, single cell - spatial transcriptomics, proteomics, metabolomics, ChIP-seq and similar, long read RNA-seq, small ...
Histotechnologist
San Francisco, CA · On-site
Prepare and process samples for spatial omics platforms, including multiplexed protein imaging and spatial transcriptomics, with both RNA- and protein-based tagging approaches * Develop, optimize ...
Quick apply
Histotechnologist
San Francisco, CA · On-site
Prepare and process samples for spatial omics platforms, including multiplexed protein imaging and spatial transcriptomics, with both RNA- and protein-based tagging approaches * Develop, optimize ...
We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics ... Provide expert guidance on biomarker study design incorporating omics and non-omics endpoints.
Quick apply
We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics ... Provide expert guidance on biomarker study design incorporating omics and non-omics endpoints.
We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics ... Provide expert guidance on biomarker study design incorporating omics and non-omics endpoints.
We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics ... Provide expert guidance on biomarker study design incorporating omics and non-omics endpoints.
Histotechnologist
San Francisco, CA · On-site
Prepare and process samples for spatial omics platforms, including multiplexed protein imaging and spatial transcriptomics, with both RNA- and protein-based tagging approaches * Develop, optimize ...
Histotechnologist
San Francisco, CA · On-site
Prepare and process samples for spatial omics platforms, including multiplexed protein imaging and spatial transcriptomics, with both RNA- and protein-based tagging approaches * Develop, optimize ...
We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics ... Provide expert guidance on biomarker study design incorporating omics and non-omics endpoints.
We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics ... Provide expert guidance on biomarker study design incorporating omics and non-omics endpoints.
... omics data integration, modeling, and analysis. Experience with single-cell technologies, spatial transcriptomics, proteomics, and epigenomics. Oncology research experience preferred but not required.
... omics data integration, modeling, and analysis. Experience with single-cell technologies, spatial transcriptomics, proteomics, and epigenomics. Oncology research experience preferred but not required.
Spatial Transcriptomics Omics information
What are the key skills and qualifications needed to thrive as a Spatial Transcriptomics Specialist, and why are they important?
To thrive as a Spatial Transcriptomics Specialist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a relevant field. Familiarity with high-throughput sequencing platforms, spatial omics technologies, and data analysis tools like R or Python is essential, along with experience using laboratory automation systems. Attention to detail, problem-solving abilities, and effective interdisciplinary communication are crucial soft skills for this role. These skills ensure accurate experimental design, robust data interpretation, and successful collaboration in cutting-edge biological research.
What are some common challenges faced by professionals in Spatial Transcriptomics Omics, and how can they be addressed?
Professionals working in Spatial Transcriptomics Omics often encounter challenges such as managing and interpreting large, complex datasets, integrating multi-omics data, and keeping pace with rapidly evolving technologies. Effective collaboration with bioinformaticians, pathologists, and laboratory technicians is essential to ensure high-quality results. Staying updated with the latest analytical tools and participating in cross-disciplinary training can help overcome these challenges and enhance both research quality and career growth.
What is spatial transcriptomics in omics research?
Spatial transcriptomics is a cutting-edge technology in the field of omics that allows researchers to measure and map gene expression within the spatial context of intact tissue sections. This means scientists can see which genes are active in specific locations of a tissue, preserving the spatial relationships between cells. By combining spatial information with transcriptomic data, researchers gain deeper insights into tissue organization, cellular interactions, and disease mechanisms. This approach is especially valuable for understanding complex tissues like tumors or brain structures.
What is the difference between Spatial Transcriptomics Omics vs Spatial Transcriptomics Technician?
| Aspect | Spatial Transcriptomics Omics | Spatial Transcriptomics Technician |
|---|---|---|
| Required Credentials | Advanced degrees (Master's/PhD) in molecular biology, genomics, or related fields | Associate's or Bachelor's degree in biology, biotechnology, or related fields |
| Work Environment | Research labs, biotech companies, academic institutions | Laboratories, research facilities, biotech companies |
| Industry Usage | Research and development, data analysis, method development | Sample preparation, data collection, equipment operation |
Spatial Transcriptomics Omics professionals focus on data analysis, method development, and research, often requiring advanced degrees. In contrast, Spatial Transcriptomics Technicians handle sample preparation and operate equipment, typically with a technical diploma or bachelor's degree. Both roles are essential in the spatial transcriptomics industry but differ in responsibilities and qualifications.
What are popular job titles related to Spatial Transcriptomics Omics jobs in California? For Spatial Transcriptomics Omics jobs in California, the most frequently searched job titles are:
What job categories do people searching Spatial Transcriptomics Omics jobs in California look for? The top searched job categories for Spatial Transcriptomics Omics jobs in California are:
What cities in California are hiring for Spatial Transcriptomics Omics jobs? Cities in California with the most Spatial Transcriptomics Omics job openings:
Computational Scientist 3, Spatial Omics & Computational Pathology
GenentechSouth San Francisco, CA • On-site
Full-time
Posted 3 days ago
Genentech rating
9.0
Based on 21 frontline employees who took The Breakroom Quiz
7th of 71 rated pharmaceutical
Job description
Job Summary:
Genentech is at the forefront of advancing spatial omics capabilities within their Research Pathology Department. They are seeking a highly skilled Computational Scientist to lead projects at the intersection of computer vision, advanced machine learning, and computational pathology, focusing on developing models and AI pipelines for spatial omics initiatives.
Responsibilities:
• Serve as the Technical Lead for computer vision, AI/ML, and multiplex imaging projects, architecting pipelines for standard whole-slide images (H&E, IHC) and high-dimensional spatial omics data.
• Design and implement cutting-edge machine learning algorithms, including foundation models and generative architectures, for image segmentation, feature extraction, and predictive modeling.
• Develop advanced multi-modal representation learning frameworks to harmonize disparate modalities—fusing morphological features with molecular data (transcriptomics/proteomics) to uncover spatial niches and cell-cell interactions.
• Engineer scalable imaging data infrastructure for large-scale image storage (e.g., OME-ZARR, OME-TIFF, SpatialData) on HPC and cloud environments.
• Embed biological priors—such as known metabolic pathways or spatial knowledge graphs—directly into the mathematical design of the AI models.
• Collaborate closely with pathologists, wet-lab, and dry-lab researchers to interpret data, visualize results, and contribute to upstream experimental design.
Qualifications:
Required:
• Ph.D in Computational Biology, Computer Science, Machine Learning, Imaging Science, Data Science, or a related highly quantitative field or a Masters Degree in these fields with 3+ years of experience may be considered.
• Demonstrated experience in computer vision, deep learning, or image processing, specifically with tissue-based or high-dimensional imaging data.
• Strong foundation in digital/computational pathology workflows and/or advanced machine learning (e.g., probabilistic modeling, representation learning, generative modeling).
• Deep proficiency in Python software engineering and extensive hands-on experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow, JAX).
• Excellent problem-solving skills with the ability to work independently as a technical lead in a multidisciplinary environment.
Preferred:
• Demonstrated experience applying machine learning to single-cell spatial transcriptomics and/or spatial proteomics analysis (e.g., 10X Genomics Xenium, Visium, Lunaphore COMET).
• Hands-on experience with multi-modal data integration, specifically combining spatial transcriptomics, proteomics, and histology datasets.
• Familiarity with the scverse ecosystem (e.g., Scanpy, Squidpy, SpatialData, scVI), computer vision libraries (OpenCV, scikit-image), and modern cloud infrastructure.
• Solid understanding of tissue histology, cell biology, and tumor microenvironments to inform model architecture.
• Experience developing agentic AI systems, LLM-driven autonomous workflows, or advanced AI-oriented tools for complex biological datasets.
Company:
Genentech is a biotechnology research company that specializes in genetic testing and personalized medicines. Founded in 1976, the company is headquartered in South San Francisco, USA, with a team of 10001+ employees. The company is currently Late Stage.
Genentech is at the forefront of advancing spatial omics capabilities within their Research Pathology Department. They are seeking a highly skilled Computational Scientist to lead projects at the intersection of computer vision, advanced machine learning, and computational pathology, focusing on developing models and AI pipelines for spatial omics initiatives.
Responsibilities:
• Serve as the Technical Lead for computer vision, AI/ML, and multiplex imaging projects, architecting pipelines for standard whole-slide images (H&E, IHC) and high-dimensional spatial omics data.
• Design and implement cutting-edge machine learning algorithms, including foundation models and generative architectures, for image segmentation, feature extraction, and predictive modeling.
• Develop advanced multi-modal representation learning frameworks to harmonize disparate modalities—fusing morphological features with molecular data (transcriptomics/proteomics) to uncover spatial niches and cell-cell interactions.
• Engineer scalable imaging data infrastructure for large-scale image storage (e.g., OME-ZARR, OME-TIFF, SpatialData) on HPC and cloud environments.
• Embed biological priors—such as known metabolic pathways or spatial knowledge graphs—directly into the mathematical design of the AI models.
• Collaborate closely with pathologists, wet-lab, and dry-lab researchers to interpret data, visualize results, and contribute to upstream experimental design.
Qualifications:
Required:
• Ph.D in Computational Biology, Computer Science, Machine Learning, Imaging Science, Data Science, or a related highly quantitative field or a Masters Degree in these fields with 3+ years of experience may be considered.
• Demonstrated experience in computer vision, deep learning, or image processing, specifically with tissue-based or high-dimensional imaging data.
• Strong foundation in digital/computational pathology workflows and/or advanced machine learning (e.g., probabilistic modeling, representation learning, generative modeling).
• Deep proficiency in Python software engineering and extensive hands-on experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow, JAX).
• Excellent problem-solving skills with the ability to work independently as a technical lead in a multidisciplinary environment.
Preferred:
• Demonstrated experience applying machine learning to single-cell spatial transcriptomics and/or spatial proteomics analysis (e.g., 10X Genomics Xenium, Visium, Lunaphore COMET).
• Hands-on experience with multi-modal data integration, specifically combining spatial transcriptomics, proteomics, and histology datasets.
• Familiarity with the scverse ecosystem (e.g., Scanpy, Squidpy, SpatialData, scVI), computer vision libraries (OpenCV, scikit-image), and modern cloud infrastructure.
• Solid understanding of tissue histology, cell biology, and tumor microenvironments to inform model architecture.
• Experience developing agentic AI systems, LLM-driven autonomous workflows, or advanced AI-oriented tools for complex biological datasets.
Company:
Genentech is a biotechnology research company that specializes in genetic testing and personalized medicines. Founded in 1976, the company is headquartered in South San Francisco, USA, with a team of 10001+ employees. The company is currently Late Stage.
What Genentech employees say
Pay
Benefits
Hours and flexibility
Workplace
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About Genentech
Sourced by ZipRecruiter
A member of the Roche Group, Genentech has been at the forefront of the biotechnology industry for more than 40 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech has multiple therapies on the market for cancer & other serious illnesses. Please take this opportunity to learn about Genentech where we believe that our employees are our most important asset & are dedicated to remaining a great place to work.
Industry
Scientific research and development services
Company size
10,000+ Employees
Headquarters location
South San Francisco, CA, US
Year founded
1976