Image Analysis Software Engineer
The Cai lab is seeking a Software Engineer. The successful candidate will help develop software platforms for performing single cell image segmentation and spatial gene expression analysis. The candidate will also help the Cai lab convert these algorithms into production ready tools for the scientific community.
The candidate’s primary role will be to help the Cai group pioneer the next generation of deep learning algorithms for single cell image segmentation and spatial gene expression analysis. Key duties and responsibilities include (but are not limited to):
- Code existing deep learning architectures and generate novel deep learning architectures for image segmentation and cell tracking through 3D images.
- Test and document the performance of different deep learning architectures.
- Construct a production ready image analysis pipeline with version control.
- Construct tutorials for cloud computing and write blog posts.
- Create interactive image analysis notebooks with Jupyter.
- Assist with crowd sourcing of data set annotation.
- Interface our deep learning based image segmentation pipeline with existing GUIs.
- Assist with GUI development.
- Assist with grant writing and paper writing.
- Assist research group members with using the created software packages.
- Collaborate with Principal Investigator to determine direction of research.
- Author or co-author results.
- Other duties as assigned.
- Bachelor’s degree in Computer Science or Bioinformatics or a related field.
- At least three years of experience working as a software developer.
- Working knowledge of Python (particularly the numpy/scipy/pandas/scikit-image/scikit-learn data science stack), Java, and C.
- Working knowledge of calculus and linear algebra.
- Familiarity with modern deep learning methods and libraries (keras/tensorflow and/or Pytorch).
- Working knowledge of modern version control packages (I.e git/github).
- Excellent oral and verbal communication skills.
- Enthusiastic about the opportunity to engage with life science researchers.
- Master’s degree in Computer Science, Bioinformatics or a related field
- Extensive deep learning experience using either Keras/tensorflow and/or Pytorch.
- Experience in computational image analysis.
- Experience in cloud computing – both Google cloud engine and Amazon web service.
- Experience in creating interactive notebooks with Jupyter.
- Experience writing online tutorials and blog posts.
- Experience creating websites.