Join the Computational Image Analysis Laboratory
Postdoctoral Research Fellow in Artificial Intelligence for Radiology Field(s) of Specialization: Computer Science, Biomedical Engineering, Electrical Engineering, or a Related Discipline
The Computational Image Analysis Laboratory is seeking a highly motivated candidate for a postdoctoral research fellow position. Since its inception in early 2002, our lab—consisting of a team of engineering scientists and physicians—has been developing and validating cutting-edge quantitative image analysis methods and, more recently, deep machine learning methods to support clinical decision-making for precision medicine. The successful candidate will participate in our active research projects to develop machine learning based methods (e.g., CNN) for automated detection, segmentation, and/or classification tasks for diagnosis, prognosis, and therapy response prediction and assessment in oncological and neurological diseases. Over the past years, the team has developed a series of state-of-the-art image analysis methods and applied these methods to numerous clinical studies. We have published several landmark papers on early tumor response assessment using the volumetric techniques and the feature and model reproducibility in radiomics, and on radiomics/AI derived imaging biomarkers for diagnosis, prognosis, and response assessment of lung cancer, hepatocellular carcinoma, and renal carcinoma, to name a few. The team has accumulated a wealth of high-quality, annotated imaging data that will further advance radiology research and practice in the era of artificial intelligence.
- Minimum Degree Required: PhD degree or equivalent
- Minimum Qualifications: Project success will require a candidate with a strong expertise in image processing algorithms, machine learning methods, computer programming languages of Python, C++, and Java, and deep learning framework of Tensorflow, PyTorch, Keras, and/or PyCaffe. Experience in medical imaging is a plus. Qualified candidates should be highly self-motivated and possess the ability to work independently as well as in a multidisciplinary collaborative environment.
- Salary and Benefits: The position is full-time with benefits. The salary is commensurate with experience.
Interested applicants should send their CV, a cover letter describing their research interests and experience, and three referees’ email and phone contact information to:
Binsheng Zhao, DSc, Director of the Computational Image Analysis Laboratory in the Department of Radiology at Vagelos College of Physicians and Surgeons of Columbia University (email@example.com).
Columbia University is an equal opportunity/affirmative action employer.