Associate Scientist

Key Responsibilities:

• Design, develop, and optimize algorithms in digital pathology analysis software packages for quantification of IHC staining expression, 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. - 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 to deliver high-quality project outcomes. - Contribute to continuous improvement of image analysis pipelines, best practices, and knowledge sharing within the team. Qualification Required:

• PhD or Masters degree in computer science, bioinformatics, electronics engineering, biological science, biomedical engineering, or related discipline. - Experience in digital pathology analysis software packages such as HALO, Visiopharm, Definiens, Inform, Fiji, and/or Aperio Image Analysis. - Hands-on experience in developing Image processing & Deep learning architectures like CNN, RNN, GAN, etc. for feature extraction, object detection, and classification. - Excellent programming skills in analytics packages such as R, Python, and/or MATLAB. Key Responsibilities: