Post-Doctoral Fellow

Job description


Anschutz Medical Campus

Colorado School of Public Health

Department of Biostatistics and Informatics


Nature of Work

The Department of Biostatistics and Informatics at the Colorado School of Public Health has an opening for a full-time Post-Doctoral Fellow. The focus of this Post-Doctoral Fellow will be the development and implementation of novel computational methods for biomedical image computing and genomic data analysis, especially integration of imaging data and genomics. The work will involve both methodological research with biostatistics/informatics faculty and collaboration with biomedical investigators. The incumbent will report directly to Dr. Debashis Ghosh and Dr. Fuyong Xing. The University of Colorado Anschutz Medical Campus is a highly collaborative campus, and the particular collaborative direction will depend on the interests of the applicant.

Specific Position Duties with Percentages of Time

Specific duties include

Research (80%)

  • Data management
  • Computational methods development
  • Exploratory data analysis
  • Biomedical image analysis
Research results (20%)

  • Presentations at conferences
  • Manuscript preparation

Salary/ Benefits:

The salary for this position is commensurate with skills and experience. The University of Colorado offers a full benefits package. Information on University benefits programs, including eligibility, is located at

The University of Colorado Denver is dedicated to ensuring a safe and secure environment for our faculty, staff, students and visitors. To assist in achieving that goal, we conduct background investigations for all prospective employees.

The University of Colorado strongly supports the principle of diversity. We encourage applications from women, ethnic minorities, persons with disabilities and all veterans. The University of Colorado is committed to diversity and equality in education and employment.

The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work. Alternative formats of this ad are available upon request for persons with disabilities.


Minimum Qualifications

  • PhD from an accredited college or university in computer science/engineering or related field at the start of the postdoc.
  • Background in machine learning, computer vision or medical image computing
  • Minimum of 2 year(s) experience in Python, Matlab or equivalent
  • Excellent communication skills (written and oral) using the English language
  • The ability to work independently on data analysis and research

Desired or Preferred Qualifications

  • Experience in development of algorithms using deep learning toolkits such as PyTorch, TensorFlow, Caffe, etc.
  • Experience in applying deep learning models to image data analysis
  • Background in high-dimensional or large-scale biological image data analysis (e.g., whole slide pathology images)

Special Instructions to Applicants:Questions should be directed to Dr. Fuyong Xing at [email protected]

Application Materials Required:Cover Letter, Resume/CV, List of References

Application Materials Instructions:A review of the application material will begin immediately and continue until the position is filled. Applicants must apply online at . Please do not submit any of your application material (via email) to the job posting contact. APPLICANTS MUST INCLUDE: 1. A cover letter which specifically addresses the job requirements and outlines qualifications 2. A current CV/resume 3. The names, addresses, daytime telephone numbers and e-mail addresses for three to five professional references in a separate document.

Job Category: Faculty

Primary Location: Aurora

Department: H0001 -- Anschutz Medical Campus - 21419 - CSPH-Bio Info General Ops

Schedule: Full-time

Posting Date: Jan 23, 2018

Closing Date: Ongoing

Posting Contact Name: Fuyong Xing

Posting Contact Email: [email protected]

Position Number: 00743013





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Job No:
Posted: 2/28/2018
Application Due: 4/29/2018
Work Type: