The Research Assistant Professor will contribute to the integrated research and teaching land-grant mission of the home unit and the Institute of Agriculture and Natural Resources (IANR) as an effective scholar and citizen, including supporting student recruitment and IANR science literacy.
Research activities for this position tie in closely with the mission of the Quantitative Life Sciences Initiative and Redox Biology Center to provide bioinformatics and computational biology research and analyses to faculty and graduate students. Responsibilities will include but are not limited to the following:
a) Next-generation sequencing analysis including differential gene expression analysis and de-novo genome and transcriptome assembly
b) Custom programming to drive analyses pipelines and integrate various data sources with analyses results
c) Continue building and providing web-based educational resources for the Redox Biology Center
d) Conduct research in redox biochemistry in collaboration with faculty in the Redox Biology Center
e) Provide professional advice to graduate students as requested
The incumbent will be expected to average .15 FTE as determined by the CASNR Academic Appointment Guidelines, and to teach in the core courses for the PhD in Complex Biosystems (LIFE891-001 and LIFE891-002). Specific course assignments may be changed over time based on the needs of the Quantitative Life Sciences Initiative and the Redox Biology Center.
In addition to the above-described duties, the individual will be expected to accept committee assignments, reporting responsibilities, and other special ad hoc assignments as requested at the administrative unit, college/division, institute, and/or university level.
Ph.D. in Computational Biology, Biochemistry, Bioinformatics, Computer Science, Statistics, or related quantitative field. 10 years experience in life science and related quantitative field. Proficiency with two programming languages required. Experience in molecular biology, biochemistry and redox biology as well as knowledge/experience in current bioinformatics tools and applications, including areas of molecular biology and biochemistry. Experience needs to be supported with publication record. Requires the ability to develop novel tools for bioinformatics research, and demonstrate the use of these tools to solve open research questions in biology. Also requires the ability to communicate knowledge to students and collaborators, and acquire new knowledge regarding developments in bioinformatics.
Please submit an electronic application via the UNL employment website employment.unl.edu/postings/55174