Responsibilities:

The Computational Biomarker Imaging Group (CBIG)  has an open postdoctoral positions. CBIG's mission is to act as a translational catalyst between computational science and cancer imaging research.

Work in our group focuses on developing innovative image analysis, machine learning, AI and data science methodologies for multimodality imaging, and also on incorporating such methods into clinically relevant applications. Most of our work to date has been on breast and lung cancer imaging, while more recently expanding more broadly in oncologic imaging and molecular imaging applications. 

A priority area is integrating imaging with genomic biomarkers towards integrated precision diagnostics for prevention and therapy for cancer. Applications focusing on radiomics and deep learning are also a priority.

We are seeking highly motivated individuals with excellent academic track-record, including first-author publications in peer-reviewed journals.  Applicants should demonstrate excellent oral and written communication skills, and the ability to work effectively independently and as part of a multidisciplinary research team.

Salary range is from $75,000 – $85,000 The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting.

Successful candidates should have, or be in the process of completing, a PhD (or equivalent) in Biomedical, Electrical or Computer Engineering, Computer and Information Science, Applied Mathematics, Statistics/Biostatistics, Bioinformatics, or related field.

Ideal applicants should have a background on biomedical image analysis, computer vision, pattern recognition and/or machine learning. Experience with Bioinformatics is a plus. Proficiency in quantitative analytical methods and computer programming (e.g., Python, C/C ) is essential. Experience with medical image analysis (e.g., MRI, CT, X-ray, Ultrasound) and related statistical methods and software packages (e.g., ITK C/C libraries, R/SPSS) is desired (but not necessary). Experience with Deep Learning is also ideal (e.g., TensorFlow, Keras, PyTorch packages, etc.).

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training.  The above hiring range represents the University?s good faith and reasonable estimate of the range of possible compensation at the time of posting.

About Columbia University

Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the university to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.

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