Sr. Scientist, Spatial Biology

NOETIK; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

NOETIK in San Francisco is seeking a Senior Scientist to drive hands-on execution, protocol development, and quality standards for spatial biology experiments on human tissue, supporting AI model training pipelines.

The role emphasizes mentorship, data QC, and cross-functional collaboration with Histology and ML teams, delivering high-quality data for scalable AI insights.

Qualifications

• PhD in molecular biology, genomics, cell biology, biomedical engineering, or related field.
• 2–5+ years of industry hands-on experience with spatial transcriptomics (CosMx, Xenium, MERFISH); CosMx preferred.
• Experience with spatial proteomics platforms and immunofluorescence panel design is highly desirable.
• Proven ability to troubleshoot wet-lab and imaging-based assay failures and trace to root cause.
• Solid knowledge of spatial transcriptomics QC metrics and data quality assessment.

Responsibilities

• Independently plan, perform and troubleshoot spatial biology experiments on human tissue samples.
• Establish and enforce data quality standards across the team's experiments and analysis pipelines.
• Mentor and train team members on technique, rigor, and quality judgment.
• Collaborate closely with cross-functional teams including Histology, and Scientific Operations to ensure seamless project execution.
• Actively participate in lab team meetings, fostering a collaborative and innovation-driven culture.
• Lead cross-functional projects with Engineering and ML Team members to design the next generation of data for AI model training.

Skills

Spatial biology expertise

In situ hybridization

Spatial data analysis

Troubleshooting

Mentorship

Organizational skills

Computational fluency

Leadership

Education

PhD in molecular biology, genomics, cell biology, biomedical engineering, or related field

Tools

CosMx

Xenium

MERFISH

Akoya PhenoCycler

Lunaphore

immunofluorescence panel design

Python

R

Job description

In this role, we are seeking a highly motivated and detail-oriented Senior Scientist to join our team at the frontier of spatial biology and AI, driving hands-on execution, protocol development, and quality standards for spatial biology experiments on human tissue samples in a lab built to fuel next-generation AI models. The ideal candidate will have deep hands-on experience with in situ hybridization & proteomics techniques, spatial data analysis, and demonstrate strong troubleshooting, mentorship, and organizational skills. This is an exciting opportunity to contribute to a multidisciplinary laboratory environment at the interface between Spatial Biology and AI model generation.

As we scale up our data generation engine, this role is focused on driving impact through day-to-day execution, troubleshooting, and quality enforcement across a high volume of runs.

KEY ROLE AND RESPONSIBILITIES

• Independently plan, perform and troubleshoot spatial biology experiments on human tissue samples.
• Establish and enforce data quality standards across the team's experiments and analysis pipelines.
• Mentor and train team members on technique, rigor, and quality judgment.
• Collaborate closely with cross-functional teams including Histology, and Scientific Operations to ensure seamless project execution.
• Actively participate in lab team meetings, fostering a collaborative and innovation-driven culture.
• Lead cross-functional projects with Engineering and ML Team members to design the next generation of data for AI model training.

REQUIRED EDUCATION & EXPERIENCE

• PhD in molecular biology, genomics, cell biology, biomedical engineering, or a related field.
• 2-5+ years of industry hands-on experience with spatial transcriptomics (CosMx, Xenium, MERFISH…); direct CosMx experience strongly preferred.
• Experience with spatial proteomics platforms (e.g., CosMx Protein, Akoya PhenoCycler, Lunaphore..) and immunofluorescence panel design are highly desirable.
• Proven ability to independently troubleshoot wet-lab and imaging-based assay failures, tracing issues back to root cause.
• Solid knowledge of spatial transcriptomics data QC metrics: transcript count distributions, segmentation quality, dropout/housekeeping-gene diagnostics, batch effects, and spatial artifacts.
• Comfortable enforcing standards across a team that includes both junior and more senior colleagues — this role requires leadership as well as technical skill.
• Excellent organizational, communication (oral and written), and documentation skills.
• Computational fluency.

Nice to have:

• Familiarity with cancer tissue biology and identity marker panels.
• Proficiency with Python or R for data analysis.
• Prior experience mentoring or informally leading junior lab staff.