Bangalore The proposed project aims to develop and validate a proof-of-concept deep learning-based Artificial Intelligence (AI) model for the detection and classification of fungal hyphae in microscopic preparations of clinical specimens, including KOH-Calcofluor and biopsy specimens. Expert-annotated microscopic images will be used to train a U-Net-based deep learning model for multi-class segmentation. The model will be validated using independent datasets, and its performance will be compared with expert interpretation. The project will also develop a prototype smartphone-based application, KOH Buddy, to provide bench-side decision support and facilitate standardized interpretation of fungal microscopy.
No of Vacancy : One
Key Responsibilities
This staff will be a pathologist who will be responsible for the curation of the relevant datasets. The staff will work under the supervision of the Co-PI Dr Aditi Goyal, in the Department of Pathology. This work will include but is not limited to
- Retrieve the relevant biopsy numbers from the Lab Information System (LIS)
- Retrieve the glass slides and blocks from the archives
- Conduct quality checks on the preparations
- Digitize them per protocols
- Anonymizing the data
- Annotating the images using the software
- Cross-checking and correction of annotations
- collection of clinical details
- Interact with the IT support
The project staff will also carry out data entry, ordering of consumables, preliminary analysis of results and reporting to the PI. They will also help with managing accounts, office work and communications Anything else required for the successful and timely completion of the project
Eligibility Criteria
Preferred Qualifications: MBBS + Post Graduate Degree (MD Pathology) including the integrated PG degrees
Age Limit: 45 Years
Preferred Language: English
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📌 Project Research Scientist-III (Medical) (Bengaluru)
🏢 St Johns Research Institute Sjri
📍 Bengaluru
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