Postdoc on Machine Learning/Deep Learning for Breast Cancer Risk Assessment

Thursday 3rd June 2021

Organization: University of Pennsylvania

Location:Philadelphia

Title: Postdoc on Machine Learning/Deep Learning for Breast Cancer Risk Assessment

Email: Despina.Kontos@pennmedicine.upenn.edu

Description:

The Computational Biomarker Imaging Group (CBIG) of the Center for Biomedical Image Computing and Analytics (CBICA) at the Radiology Department at the University of Pennsylvania has 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 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 imaging, while more recently expanding more broadly in oncologic imaging and molecular imaging applications. A priority area is integrating imaging with genomic biomarkers towards precision medicine prevention and therapy for cancer. Applications focusing on radiomic analysis and deep learning are also priority areas for our research. The specific position will focus on developing and evaluating novel imaging biomarkers for breast cancer risk assessment using radiomics analysis and deep learning approaches on 3D digital breast tomosynthesis (DBT) imaging.

Postdoctoral Position Qualifications:
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 or related field. Ideal applicants should have a background on biomedical image analysis, computer vision, pattern recognition and/or machine learning. 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) or statistical methods and software packages (e.g., ITK C/C++ libraries, R/SPSS) is a plus. 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.

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 Biomedical Image Computing and Analytics (CBICA), the Abramson Cancer Center (ACC), the Penn Institute for Biomedical Informatics (IBI), and the Center for Clinical Epidemiology and Biostatistics (CCEB).

For more information, please visit:

Computational Biomarker Imaging Group (CBIG): http://www.uphs.upenn.edu/radiology/research/labs/cbig/

Center for Biomedical Image Computing and Analytics (CBICA): http://www.cbica.upenn.edu/

Penn Institute for Biomedical Informatics (IBI): http://upibi.org/

Abramson Cancer Center (ACC): https://www.pennmedicine.org/cancer

Center for Clinical Epidemiology and Biostatistics (CCEB): http://www.cceb.upenn.edu/

Penn Biomedical Postdoctoral Programs: http://www.med.upenn.edu/postdoc/

For more details and to apply contact:

Despina Kontos, Ph.D.
Associate Professor
Director, Computational Biomarker Imaging Group (CBIG)
Center for Biomedical Image Computing and Analytics (CBICA)
University of Pennsylvania, Department of Radiology
Bioengineering, Biostatistics and Epidemiology Graduate Groups
Senior Fellow, Institute for Biomedical Informatics (IBI)

Applications should include a letter of motivation, a curriculum vitae, and names and addresses of three references. The University of Pennsylvania is an equal opportunity employer.