Postdoc on Machine Learning & AI in Cancer Imaging

Friday 15th October 2021

Organization University of Pennsylvania

Location Philadelphia

Title Postdoc on Machine Learning & AI in Cancer Imaging

URL https://www.indeed.com/job/postdoc-machine-learning-ai-medical-imaging-univ-pennsylvania-f532f4f178e26ef6

Email Address 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, 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 molecular and genomic biomarkers towards integrated precision diagnostics for prevention and therapy for cancer. Applications focusing on radiomic approaches and deep learning are also priority areas for our research.

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, 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.

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/

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.