Columbia University
The Computational Biomarker Imaging Group (CBIG), led by Dr. Despina Kontos, of the Center for Innovation in Imaging Biomarkers and Integrated Diagnostics (CIMBID) at the Radiology Department at the Columbia University Vagelos College of Physicians and Surgeons, has an open position for an Associate Research Scientist. 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, artificial intelligence 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.
Successful applicants will join a vibrant research environment and will work closely both with computational scientists and clinical investigators. Collaborators include faculty in our Radiology department, the Center for Innovation in Imaging Biomarkers and Integrated Diagnostics (CIMBID), the Herbert Irving Comprehensive Cancer Center (HICCC), the Department of Biomedical Informatics (DBMI), the Department of Biomedical Engineering (BME) and across the Columbia University Irving Medical Center (CUIMC).
We are seeking highly motivated individuals with excellent academic track-record, including first-author publications in peer-reviewed journals. 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.). Applicants should demonstrate excellent oral and written communication skills, and the ability to work effectively independently and as part of a multidisciplinary research team.
Educational Requirements:
PHD
2-4 years of postdoctoral research experience
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.
Successful applicants will join a vibrant research environment and will work closely both with computational scientists and clinical investigators. Collaborators include faculty in our Radiology department, the Center for Innovation in Imaging Biomarkers and Integrated Diagnostics (CIMBID), the Herbert Irving Comprehensive Cancer Center (HICCC), the Department of Biomedical Informatics (DBMI), the Department of Biomedical Engineering (BME) and across the Columbia University Irving Medical Center (CUIMC).
We are seeking highly motivated individuals with excellent academic track-record, including first-author publications in peer-reviewed journals. 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.). Applicants should demonstrate excellent oral and written communication skills, and the ability to work effectively independently and as part of a multidisciplinary research team.
Educational Requirements:
PHD
2-4 years of postdoctoral research experience
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.