Develop and maintain an AI-driven pathology platform to quantify biomarker expression from Whole Slide Images (WSIs) using deep learning algorithms.
Requirements
- deep learning algorithms
- biomarker quantification
- HandE and IHC-stained slides
- machine learning
- deep learning techniques
- biomedical image analysis
- Genome-Wide Association Study (GWAS)
- SNPs
- statistical hypothesis testing
- computational tools
Responsibilities
- Develop and maintain an AI-driven pathology platform to quantify biomarker expression from Whole Slide Images (WSIs) using deep learning algorithms.
- Automate biomarker quantification from HandE and IHC-stained slides to enhance prediction accuracy, reduce manual workload, and improve diagnostic traceability.
- Apply machine learning and deep learning techniques to biomedical image analysis.
- Conduct GWAS to identify SNPs related to obesity, hypertension, and other chronic conditions.
- Perform statistical hypothesis testing and interpret biological significance to refine gene candidate lists.
- Automate repetitive research tasks to improve lab efficiency.
- Develop scripts and computational tools for tasks such as siRNA sequence modifications for patent purposes.
Other
- Masters Degree in Biomedical Informatics, or Biochemistry
- Provide weekly updates with visualizations and technical explanations of model performance.
- Communicate complex AI and bioinformatics concepts clearly to technical and non-technical audiences.
