Description: The digital pathology group is looking for students with image and data analysis experience to support translational bioinformatics with algorithm development, validation and implementation skills. During the internship, students will gain valuable experience working with image analysis team within the translational medicine organization, processing and analyzing digitized pathology whole slide images. Bristol-Myers Squibb is a global biopharmaceutical company whose mission is to discover, develop and deliver innovative medicines that help patients prevail over serious diseases.
- Hands-on support of pathology whole slide image analysis tools and technology
- Working alongside image scientists in the digital pathology group to manage, prepare and analyze pathology whole slide images to support Immuno-Oncology and other disease areas.
- Performing analytics of associating image analysis results with response and survival data.
- Active participation in the testing of pathology image management and analysis systems, tools and technology
- Prepare and present findings from image analysis projects to other groups within BMS.
- Collaborate with other image scientists to propose, review and finalize future image analysis algorithm development and project work.
Prefer a responsible undergraduate, graduate or post-graduate information science, bioinformatics and/or computational biology, applied mathematics, biomedical engineering or computer science degree with technical aptitude.
The desired candidate should have excellent skills using MATLAB, R, and/or Python to develop custom image analysis algorithms and perform basic statistical analysis.
Prior experience in one or more pathology image analysis platforms such as HALO, Visiopharm, Definiens, and/or InForm is desirable.
A high degree of organization and self-motivation is required.
Candidate should be capable of managing relationships within project teams. For example, he/she should be able to coordinate with all peers involved to ensure the completion of the associated work.