Deep Learning for Microscopy Image Analysis

I'm seeking a professional skilled in data science deep learning and image processing to help in developing the QC software for fluorescent microscopy images . The primary goal is to evaluate the quality of signal quantitation for segmented objects.

The software currently exists in the form of python notebooks and is mostly based on existing python libraries (scanpy, mesmer, spacec, deepcell etc). 1) We need to incorporate and test deep learning (autoencoder) based object quantification modalities. 2) Clean up the code and refine some of the existing functions. 3) write up html/pdf report generation 4) Wrap the code with Java or C++ GUI and convert it into a license protected executable.

Key Responsibilities:
- Develop and implement deep learning methods to signal quantitation of segmented objects
- Focus on enhancing accuracy for signal quantitation

Ideal Skills:
- Proficiency in deep learning (autoencoders R-CNN etc) and image processing
- data science python, statistics

Plus:
- Java
- C++
- AI – langchain, OpenAI API

requirements: ability to sign NDA and consulting agreement.
preferred communication mode: video–conferencing