Associate Scientist
biospace
Job Description
- Design, develop, and optimize algorithms in one or more digital pathology analysis software packages for quantification of IHC staining expression, including tumor/stroma classification and cellular feature extraction.
- Apply strong proficiency in Python programming to support image analysis workflows, data processing, and model development.
- Train, evaluate, and deploy transformer-based deep learning models for image analysis and inference, with an understanding of model performance and limitations.
- Perform statistical analyses and data visualization using Power BI, R, Python, and/or MATLAB to derive actionable insights from image-derived data.
- Document algorithms, analyses, methodologies, and results in a clear and detailed manner, ensuring compliance with internal quality standards and regulatory requirements.
- Collaborate effectively within cross-functional teams comprising pathologists, scientists, and fellow image analysts to deliver high-quality project outcomes.
- Demonstrate strong interpersonal and communication skills, enabling productive collaboration with diverse stakeholders across disciplines.
- Contribute to continuous improvement of image analysis pipelines, best practices, and knowledge sharing within the team.