Computational Image Analysis Scientist 2D/3D Biomedical Imaging

Our client is a global, research-driven pharmaceutical manufacturer focusing on treatment options for diseases and conditions for which there is no satisfactory treatment option to date. The company is looking for a Computational Image Analysis Scientist•2D/3D Biomedical Imaging to join the team. This is an amazing opportunity to work on cutting edge treatments and make a difference!

Job Title:

Computational Image Analysis Scientist•2D/3D Biomedical Imaging Pay rate : $39/hr•$42/hr.

Location:

Ridgefield, CT Job type : 2-year contract Position Summary We are seeking a Computational Image Analysis Scientist to develop, optimize, and apply advanced image analysis workflows for 2D and 3D biomedical imaging data. The role focuses on quantitative analysis of histology, immunohistochemistry (IHC), immunofluorescence (IF), and multiplex imaging datasets to support biomarker discovery, translational research, and preclinical/clinical studies. The ideal candidate combines strong programming and machine learning expertise with hands-on experience in digital pathology and a collaborative mindset for working with multidisciplinary scientific teams. Key Responsibilities Develop, implement, and optimize image analysis pipelines for 2D and 3D biomedical imaging datasets Perform quantitative analysis of histology, IHC, IF, and multiplex imaging (mIF) data Apply classical image processing and machine learning methods for: Image segmentation Feature extraction Cell detection and classification Analyze and quantify spatial biology and cellular phenotypes from tissue imaging data Integrate and work across digital pathology platforms including: HALO AI Visiopharm QuPath CellProfiler Collaborate closely with pathologists, biologists, and data scientists to define analytical endpoints and experimental design Validate image-derived biomarkers and ensure scientific and analytical rigor Document workflows to ensure reproducibility and regulatory-grade traceability Support interpretation, visualization, and presentation of imaging-derived data for scientific reports and publications Enable cross-lab collaboration through transfer of image analysis workflows and algorithms Required Qualifications Bachelor's degree with 3+ years of experience, or Master's degree in a relevant scientific discipline (or equivalent experience) Strong proficiency in Python and/or R for scientific computing and data analysis Demonstrated experience in machine learning applied to image data Hands-on experience with digital pathology or biomedical image analysis Experience working with H&E, IHC, and multiplex immunofluorescence (mIF) datasets Proven ability to perform cell segmentation, classification, and marker quantification Experience using at least one digital pathology or image analysis platform (e.g., HALO, Visiopharm, QuPath, CellProfiler) Strong problem-solving skills and ability to work independently in a research-driven environment Preferred Qualifications Experience in tumor immunology, histopathology, or spatial biology Prior experience in biotech, pharmaceutical, or industry research environments Familiarity with advanced spatial or multiplex imaging technologies INDBH #LI-AH1