This job has Expired
Postdoctoral Research Associate
GENERAL REQUISITION INFORMATION
|EEO Statement:|| |
UNMC is an Affirmative Action Equal Employment Opportunity Employer, including an equal opportunity employer of protected veterans and individuals with disabilities.
|Department||Genetics Cell Biology & Anatomy 50000507|
|Business Unit(College/Institute)||College of Medicine|
|Work Schedule||8:00am - 5:00pm|
|Requisition Category||Research - Academic|
|Requisition Title||Postdoctoral Research Associate|
|Job Title/Academic Rank||Postdoctoral Research Associate|
|Additional Requisition Title|
|Appointment Type||A1 - REG OTHER ACAD SAL|
|Salary Range||Salary Commensurate with Experience|
|Job/EEO Category||Professional Non-Faculty (Includes Other Academic)|
|Job Requisition Begin Date||03/31/2023|
|Position Summary|| |
The Department of Genetics, Cell Biology and Anatomy at the University of Nebraska Medical Center is seeking a POST DOCTORAL RESEARCH ASSOCIATE to pursue exciting research in Bioinformatics and Machine Learning. The incumbent will apply machine learning and deep learning tools to integrate, analyze, and correlate multi-omics data generated from genomic, epigenomic, transcriptomic and proteomic, and crystallography experiments, write manuscripts and assist in grant writing. Additional opportunities to teach and mentor graduate students are available. Dr. Babu Gudaís computational biology laboratory offers interactive environment and resume building opportunities through collaborations and co-authorships on a wide array of research projects associated with the analysis of genomic big data.
|Required Qualifications|| |
Ph.D. in Bioinformatics, Computer Science or in a related field with strong and relevant publication record. Excellent programming skills in Perl/Python and R are required.
|Supplemental Qualifications|| |
Working knowledge of Linux-based systems, high-performance computing (HPC), machine learning packages such as Scikit and Keras, next-generation sequencing data analysis, web programming, and relational databases is preferred. Prior training in life sciences research and training in statistics would be a plus.
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