High Content Image Analysis-Trainee - Axle Informatics

The National Center for Advancing Translational Sciences (NCATS) works towards transforming the translational process so that new treatments and cures for disease can be delivered to patients faster. Translation is the process of turning observations in the laboratory, clinic and community into interventions that improve the health of individuals and the public.

NCATS research groups extensively utilize automated microscopy equipment and high-content analysis (HCA) methods for cell-based drug discovery campaigns. These technological approaches enable the high throughput testing of novel pharmaceutical compounds in mammalian cellular model systems. HCA approaches rely on computational algorithms to measure changes in cellular behavior that are recorded in digital micrograph images. Along with other orthogonal experimental approaches, the HCA projects push forward the primary institutional goal of NCATS, which is to increase the rapid translation of fundamental biological understanding into clinical therapies that directly benefit patients.

Internship Program at Axle Informatics/NCATS

The recruiting team is driven by the passion to recognize emerging talent. Our program places the best students in positions that they will grow both technically and personally through their experience working closely with their Manager, Mentor, and team. We are dedicated to providing an experience that allows for the intern to experience life at NCATS by giving them projects that are critical to their team’s success.

Instead of going on coffee runs and making copies, you’ll be seated at the table making critical decisions that will influence not only your team, but the overall achievement of NCATS’s mission.

About the team

The supports multiple NCATS research groups at all stages of HCA/HCS project progression, including 1) consulting regarding assay miniaturization and cellular sample preparation, 2) guidance for optimized HCS instrument operation and high-throughput microscopy digital image acquisition, 3) optimization of automated image analysis algorithms from both commercial and open source software as well as training for use of these computational tools, 4) training for usage of commercial and customized computational tools for statistical comparison and graphical visualization of numerical results from differentially treated cellular samples. To accomplish these tasks, the HCA Services Team uses a multidisciplinary approach. Data scientists, digital image analysists, and microscopist team members work collaboratively to assist NCATS biologists with their HCA projects.

As a high content image analysis intern, you will be helping NCATS biologists measure changes in cell morphology during pharmaceutical discovery/development campaigns. Diverse cellular assays require the customization and testing of automated image analysis algorithms (both commercial software-based, and also open source code), and you work alongside current HCA Services Team members to complete these tasks. In addition, you will help to organize imaging data sets and corresponding experimental metadata. You may also help to manually identify changes in cellular and subcellular structures due to chemical treatment and establish ‘ground truth data sets’ for training/testing of new image analysis algorithms.

This will include (but not be limited to) the following:

Matching the needs of needs of NCATS biologists with best option for image analysis considering project time frame and budget, image complexity, throughput requirement, biological question/hypothesis, etc. Both classical image analysis and machine learning-based image analysis options will be considered. Analysis based on hierarchical single-cell segmentation, and subcellular feature segmentation will likely be preferred, but whole image analysis options may also be explored.

1. Commercial guided workflow image analysis software options

• Specific HCA instrument-linked image analysis software
• Columbus image analysis server software (Perkin Elmer)
• Imaris software (BitPlane)

2. Commercial customizable image analysis software options

• Matlab (Mathworks, Inc.) prototype scripting environment
• Matlab published image analysis routines

3. Open source customizable image analysis software options. 

• Open source scripting (Python, R,Jupyter Notebooks, etc)
• Published open source analysis routines

• Currently working toward a bachelors or masters degree in datascience, bioinformatics, biomedical engineering, or related biological sciences (cell biology, molecular biology, microbiology, etc). Preference will be given to those having some combined experience with biomedical sciences and analytical approaches.
• Basic knowledge of applied mathematics, statistics, principles of machine learning. Direct experience with digital image analysis or computer vision approaches is useful, but not required.
• Hands on experience with creating and debugging analytical scripts (Python, R, Matlab, etc).
• Major interest in solving complex, time-critical problems.
• Strong verbal and written communication skills