Skip Navigation
client logo
Medical College of Wisconsin Careers

Job Details

Postdoctoral Fellow
  • Requisition ID #: 31408
  • Job Category: Research
  • Employment Type: Full Time
  • Experience Level: Postdoctoral
  • Salary Grade:
  • Work Location: Medical Education Building
  • Department: Institute for Health and Equity
  • Division: Biostatistics
  • Education: Doctorate Degree

Position Description:

This post-doctoral level position will contribute to fundamental advances in the analysis of large-scale, complex genetic and genomic datasets with a focus on cancer and hematologic traits. The postdoc will be involved in both applied projects in Genetic Epidemiology as well as methodological projects in Statistical Genetics. We seek a highly collaborative individual that excels in a team environment and that can contribute to multiple projects simultaneously.

The postdoc will be supervised by Dr. Paul Auer and will work with other members of the Auer lab to advance research in statistical genetics. Opportunities for professional development abound at the Medical College of Wisconsin, and the postdoc will be expected to establish an individual develop plan that incorporates the postdoc’s career and training goals with the research goals of the Auer lab. Throughout the appointment, the postdoc will be expected to gain independence.

Primary Functions

  • Plan, design and implement novel statistical approaches to analyzing large-scale genetic data.  
  • Participate as a statistical analyst on large-scale genetic and genomic studies with responsibilities ranging from designing studies, to developing analysis plans, and conducting sophisticated and cutting-edge data analyses.
  • Contribute to science through both independent and collaborative research, including co-authoring and (in some cases) lead-authoring papers. Assist in outcome interpretation and composition of the results sections of manuscripts and reports.
  • Communicate results to collaborators and larger scientific audiences at research conferences.
  • Lead efforts to apply novel statistical methodologies related to the genetic and genomic epidemiology of cancer.
  • Regularly review the latest research methodologies in statistical genetics and develop plans for implementation.
  • Implement reproducible research standards, including sharing code and using version control software.
  • Participate in regular meetings with the principle investigator, research staff, and collaborators.  

Preferred Schedule:
Normal Business Hours

Position Requirements:

Minimum Required Education:               PhD in Statistics or closely related field

Minimum Required Experience:              None

Preferred Experience:                           

  • Advanced statistical programming skills (e.g., R, Python)
  • Familiarity with a basic programming language (e.g., C, Java)
  • Experience with a High Performance Computing cluster
  • Familiarity with standard command line tools and pipelines for genetic and genomic data analysis (e.g., PLINK, kallisto, BEDTools, GENESIS)
  • Experience implementing reproducible research, including sharing code and using version control software
  • Basic knowledge of population genetics
  • Basic knowledge of Cancer Epidemiology

MCW as an Equal Opportunity Employer and Commitment to Non-Discrimination
The Medical College of Wisconsin (MCW) is an Equal Opportunity Employer. We are committed to fostering a diverse community of outstanding faculty, staff, and students, as well as ensuring equal educational opportunity, employment, and access to services, programs, and activities, without regard to an individual's race, color, national origin, religion, age, disability, sex, gender identity/expression, sexual orientation, marital status, pregnancy, predisposing genetic characteristic, or military status. Employees, students, applicants or other members of the MCW community (including but not limited to vendors, visitors, and guests) may not be subjected to harassment that is prohibited by law or treated adversely or retaliated against based upon a protected characteristic.