Medical Image Analysis Researcher

Team Description: Kitware's Medical Computing team solves complex healthcare challenges through customized software solutions. The team provides research, development, and technology integration services to research centers, universities, and companies in the medical and biomedical sectors. By joining our team you will participate in a dynamic multidisciplinary work environment with exceptionally talented computer scientists, software engineers, mechanical engineers, and biomedical engineers. 
About the Projects: We build powerful software solutions using our well-established open source platforms including VTK, ITK, 3D Slicer, Pulse, CMake, and ParaView. These platforms are mature, supported, documented, and thoroughly tested software systems that are in use by tens of thousands of developers and end-users worldwide. Our commercial projects involve generating solutions for medical device companies from ultrasound and preclinical imaging companies, to surgery device companies. Our research projects involve collaborations with top research institutions, including Harvard Medical School, MIT, Cleveland Clinic, Duke University, UNC-Chapel Hill, and others, and build on our open source platforms.

In This Position You Will:

• Develop advanced image analysis and machine learning algorithms that will be deployed as part of software applications for medicine that are used by people and customers, every day, around the world.
• Extend the capabilities of MONAI, ITK, and 3D Slicer to meet the needs of academic and commercial users as they investigate new medical procedures and imaging systems, release innovative products, and improve all aspects of patient care.
• Collaborate with world-class coworkers and external collaborators on dynamic, fast-paced projects.

Required Qualifications:

• Ph.D. in Computer Science or related field with emphasis in medical image analysis and machine learning.
• Highly innovative and demonstrated track record for solving difficult technical challenges using medical image analysis algorithms.
• Possess a strong foundation in classical image registration and segmentation techniques, as well as expertise in modern deep learning-based approaches for image analysis.
• Strong publication record in relevant journals and conferences such as (but not limited to) TMI, MICCAI, SPIE MI, ISBI, and/or IPMI.
• Familiarity with open-source toolkits and applications for medical image analysis and machine learning such as ITK, Slicer, scikit-learn, MONAI, and/or PyTorch.
• Experience programming in C/C++ and Python.

Preferred Qualifications:

• Demonstrate advanced expertise in ultrasound imaging, including acquisition, image generation, and analysis.
• Proven track record of conducting research and contributing methodologies and code implementations to open-source platforms, showcasing a commitment to collaborative development and practical implementation.