Histotechnician

Lancesoft; Ridgefield (CT); On-site; USD 90,000 - 140,000; Full time

Job summary

Lancesoft in Ridgefield, CT is seeking a Histotechnologist / Spatial Biology Specialist to join the Discovery Research team. This role will help develop and expand spatial biology capabilities for preclinical and translational biomarker discovery, combining histology, imaging, and data analysis.

You will develop and optimize high-plex tissue-based assays, design antibody panels, and support spatial transcriptomics with QC, collaborating with computational scientists to integrate spatial data

Qualifications

• Experience with high-plex/multiplex protein imaging in human and/or mouse tissues.
• Experience with spatial transcriptomics or related spatial gene-expression technologies.
• Experience with quantitative microscopy or high-content tissue imaging.
• Experience with image analysis including tissue annotation, cell segmentation, phenotyping, spatial measurements, or quantitative biomarker analysis.
• Familiarity with R, Python, or other data-analysis environments.

Responsibilities

• Develop, optimize, and execute high-plex tissue-based assays in human and mouse tissues.
• Design and optimize multiplex antibody panels, including antibody selection, staining conditions, controls, panel compatibility, tissue-specific optimization, and assay performance.
• Support establishment and application of spatial transcriptomics and emerging spatial profiling technologies, including assay and data QC.
• Develop workflows spanning tissue preparation, staining, imaging, spatial profiling, and quantitative analysis; troubleshoot to improve robustness and data quality.
• Support acquisition and analysis of whole-slide, multiplex, and spatial imaging datasets, including tissue annotation, cell segmentation, phenotyping, and spatial quantification.
• Collaborate with computational scientists and project teams to integrate spatial protein, RNA, imaging, and histopathology data.
• Contribute to a collaborative environment emphasizing scientific rigor, data quality, and continuous improvement.

Skills

High-plex imaging

Antibody panel design

Spatial transcriptomics

Quantitative image analysis

Tissue annotation

Cell segmentation

Phenotyping

Spatial measurements

Biomarker analysis

R/Python familiarity

Education

Bachelor's or Master’s degree in Biology/Histotechnology/Biomedical Sciences or related

Tools

R

Python

Job description

Duties: The Oncology Research department at the client is seeking a Histotechnologist / Spatial Biology Specialist to join the Discovery Research team in Ridgefield, CT. This role will support the development and expansion of spatial biology capabilities for preclinical and translational biomarker discovery. The successful candidate will combine a strong foundation in histology and tissue-based assay development with experience in high-plex spatial technologies and quantitative image analysis. The position will play an important role in developing and optimizing high-plex protein staining panels in human and mouse tissues, implementing spatial transcriptomic workflows, and generating high-quality spatial datasets that enable deeper characterization of the tumor microenvironment and tissue biology. This is an ideal opportunity for a scientist who enjoys working at the interface of histology, imaging, and data analysis. We are particularly interested in candidates who can bridge wet-lab experimentation with quantitative approaches and who are excited about establishing and advancing new spatial biology capabilities.

Key Responsibilities

Spatial Biology & Assay Development

• Develop, optimize, and execute high-plex tissue-based assays, including multiplex immunofluorescence and other spatial protein profiling approaches in human and mouse tissues.
• Design and optimize multiplex antibody panels, including antibody selection, staining conditions, controls, panel compatibility, tissue-specific optimization, and assay performance.
• Support the establishment and application of spatial transcriptomics and emerging spatial profiling technologies, including assay and data QC.
• Develop integrated workflows spanning tissue preparation, staining, imaging, spatial profiling, and quantitative analysis, troubleshooting assays to improve robustness, reproducibility, and data quality.
• Support acquisition and analysis of whole-slide, multiplex, and spatial imaging datasets, including tissue annotation, cell segmentation, phenotyping, spatial quantification, and visualization.
• Collaborate with computational scientists and project teams to integrate spatial protein, RNA, imaging, and histopathology data.

Histology & Tissue Processing

• Perform core histology workflows, including tissue processing, embedding, microtome sectioning, slide preparation, H&E, IHC/IF, ISH, and coverslipping.
• Work with human and mouse FFPE and frozen tissues, optimizing tissue preparation and sectioning for advanced spatial assays.
• Perform QC of tissue sections, staining, imaging, and spatial assays to ensure reproducible, high-quality data.

Laboratory & Cross-Functional Support

• Operate instrumentation supporting histology, multiplex staining, imaging, slide scanning, and spatial biology workflows.
• Maintain accurate experimental records, protocols, SOPs, assay-development documentation, and sample tracking.
• Communicate results and technical recommendations and collaborate across in vivo pharmacology, pathology, translational research, molecular biology, imaging, and computational sciences.
• Contribute to a collaborative environment emphasizing scientific rigor, innovation, data quality, and continuous improvement.

Skills: Preferred Qualifications

Candidates do not need to bring every capability listed below. We are particularly interested in individuals with complementary wet-lab and image analysis who are motivated to broaden their expertise in spatial biology.

• Experience with high-plex/multiplex protein imaging and antibody panel development in human and/or mouse tissues.
• Experience with spatial transcriptomics or related spatial gene-expression technologies.
• Experience with quantitative microscopy or high-content tissue imaging.
• Experience with image analysis, such as tissue annotation, cell segmentation, phenotyping, spatial measurements, or quantitative biomarker analysis.
• Familiarity with R, Python, or other data-analysis/programming environments.

Education:

Bachelor s or Master s degree in Biology, Histotechnology, Pathology, Biomedical Sciences, or a related discipline.