Postdoctoral Scholar - Public Health Sciences

Postdoctoral Scholar of Machine Learning and Statistical Genomics

The Department of Public Health Sciences is seeking a postdoctoral scholar. The overall goal is to: (1) develop and apply statistical genomic methods to analyze multi-omics datasets for understanding complex disease etiology and (2) develop and apply novel statistical models to analyze EHR data. The postdoctoral fellow, under the mentorship of Dr. Dajiang Liu ((Use the "Apply for this Job" box below).), is expected to work on at least one of these objectives.

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

This is a term position; length of the term will be discussed during the interview process. Continuation past the term length discussed will be based on university need, performance, and/or availability of funding.

• A Ph.D. in statistics/biostatistics, computer science, bioinformatics, or other related disciplines is required.
• Strong interest, research background and experience in the methodology research in statistical genomics, machine/deep learning, bioinformatics methods in
  -omics data are preferred.
• Demonstrated evidence of excellent programming, collaboration, and communication skills.

• reviewing literature,
• designing and implementing methods,
• analyzing data, summarizing study results, and
• drafting manuscripts.

They will work closely with our team to publish research findings in high-impact journals and present at scientific conferences.

Employment with the University will require successful completion of background check(s) in accordance with University policies.

Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional well-being.

For more detailed information, please visit our Benefits Page. (

Note:

For Postdoctoral benefits, please see our Postdoctoral Benefits page.)

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The ASR is available for review here.

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