Deep Learning Expert Needed for Stem Cell Classification Using CNNs

I am seeking an expert in deep learning and computer vision to assist with a stem cell classification project. The project involves working with images in three modalities: phase-contrast, GFP, and DAPI. The key tasks include:

1. Cell Segmentation:
- Manually annotate and create accurate masks for individual cells, separating them from the background and cell clusters.

2. Classification:
- Perform binary classification of cells into pluripotent vs. non-pluripotent categories.
- Further classify pluripotent cells into three sub-classes: low, mid, and high pluripotency.

Deliverables:
- A fully annotated dataset with masks and class labels for all cells.
- Segmentation pipeline/code used to generate the masks.
- At least three CNN models trained and evaluated on the dataset, achieving ≥ 93% accuracy if possible.
- Evaluation metrics (accuracy, precision/recall, confusion matrices) for each model.
- A comparison of the models with justification for the best-performing one.
- Well-documented training/inference code with instructions to run it.
- A written report detailing the dataset, methods, experiments, and results.
- Presentation slides summarizing the project (suitable for academic use).

Timeline: 2–3 months from the start date.

Budget: $400–$600 USD (depending on experience and scope).