Teams at Merge Labs

Lead the design and deployment of large-scale bioinformatics and omics pipelines spanning genomics, transcriptomics, and proteomics. Integrate multimodal biological data with machine learning, develop reproducible analysis frameworks, benchmark predictive models, and collaborate with wet-lab scientists to guide molecular engineering and experimental campaigns. Contribute novel computational biology algorithms, research roadmaps, and scientific leadership.

Develop and maintain shared computational imaging software that converts ultrasound data into image series. Build and optimize beamforming, filtering, motion estimation, and reconstruction methods for real-time and large-scale processing. Validate performance through benchmarks, regression tests, uncertainty analysis, and reproducible experiments. Improve GPU and memory efficiency, establish device requirements, and evaluate learned imaging methods while collaborating with scientists and engineers.

Develop and maintain Python-based image-analysis workflows for registration, detection, background subtraction, drift correction, and response measurement. Validate accuracy and repeatability using controls and regression tests, align ultrasound with MRI and anatomical references, and integrate methods with acquisition and reconstruction systems. Optimize processing for large datasets while providing documented tools scientists can use independently.