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Mandatory Key Skills:
1. Proficient in training machine learning models specifically for disease detection using ophthalmology images, such as Fundus images and Optical Coherence Tomography (OCT).
2. Knowledge and understanding of CNN, Transformers and other related algorithms.
3. Familiarity with computer vision libraries and frameworks such as OpenCV, TensorFlow, PyTorch, Keras, Scikit-learn, and Scikit-image.
Responsibilities:
1. Design and develop machine learning models for disease detection using ophthalmology images, including Fundus images and OCT.
2. Extract features and preprocess the ophthalmology images to optimize the performance of the machine learning models.
3. Collaborate with the research team to identify relevant datasets and create accurate training data.
4. Train and fine-tune the machine learning models using state-of-the-art algorithms and techniques.
5. Evaluate and validate the performance of the machine learning models on both internal and external datasets.
6. Continuously improve the accuracy and efficiency of the disease detection models through experimentation and fine-tuning.
7. Stay updated with the latest advancements and research in the field of ophthalmology and machine learning for better optimization of models.
8. Work closely with cross-functional teams to integrate the developed models into existing applications or systems.
Full Time,Permanent
Software
AI/ML, DICOM, FHIR
Other Graduate