The client requires the services of a computational research scientist with experience in biomedical image processing and machine learning, in particular deep learning, who will be responsible for supporting R&D projects in medical image analytics and clinical decision making. The ideal applicant has a strong background in deep learning demonstrated through publications in leading journals and conferences. The applicant should be comfortable with both Windows and Linux environments, and programming in MATLAB and Python. In addition, the applicant must be familiar with common software libraries for deep learning, such as TensorFlow and Keras. Ideally, the applicant has already applied these libraries for medical decision support in radiographical images, in particular X-rays and CTs. Experience in the use of high performance clusters with GPUs for solving complex problems is preferable.
The candidate will be a part of the medical image analytics R&D program. The selected candidate shall conduct R&D using deep learning applied to medical image and text data for developing novel solutions in support of clinical decision-making, and multimodal information retrieval. A focus will be on processing radiological data for detecting manifestations of tuberculosis and drug-resistance.
: Clinical Decision-Making, Deep Learning, GPU, Keras, Linux, Machine Learning, MATLAB, Medical Image Analytics, Python, Radiological Imaging, TensorFlow, Windows
Required Skills and Experience
Required Professional and Personal Qualities
- Ph.D. in Computer Science, Computer Engineering or related technical discipline, and demonstrable experience in image analysis and machine learning.
- Demonstrable experience in medical image processing, analysis, and classification.
- Demonstrable experience in developing custom deep learning workflows.
- Demonstrable experience in traditional machine learning techniques, e.g. Support Vector Machines (SVMs), applied to medical image analytics.
- Publications in high-quality journals in applying deep learning to medical imaging problems for clinical decision-making.
- Experience with statistical analysis of experimental outcomes.
- Experience with use of multiple GPUs on desktop as well as high-performance GPU compute clusters for deep learning.
- Programming in MATLAB, Python, and at least one common deep learning library.
- Experience with container technologies: Singularity, Docker.
- Good working knowledge of DICOM format is a plus.
- Strong organizational skills.
- Ability to write clean, consistent, and well-documented code.
- Excellent team and interpersonal skills. Ability to both take direction and work in a self-directed manner, as well as in a collaborative team environment.
- Excellent oral and written communication skills, and ability to document projects and provide status reports. Experience in presenting work at leading national and international forums is desirable.
- Experience in mentoring students is desirable.