Scholarship: Fully funded
Degree: PhD
Nationality: International Students
Location: USA
Application deadlines: Open
Scholarship Description:
Work in the group involves using multi-omics data, mathematical models and machine learning to produce useful biological information and concepts that current theories cannot provide. Examples of the biological topics include functions of non-coding RNAs in mammalian cells, pattern formation of motor neurons, differentiation of immune cells, and gene regulatory networks in plants. All of these projects are in close collaborations with experimentalists. The group is interested in developing theories and data analytical methods that are broadly useful in biology. More information about the research group can be found at http://www.tianhonglab.org.
Located near the beautiful Smoky Mountains, The University of Tennessee, Knoxville (UTK) was founded in 1794 and is one of the oldest public universities in the country. UTK is a vibrant and diverse urban campus, located in the heart of Knoxville. It is the flagship campus for the UT system, a participating institution of the Association of Public and Land-grant Universities (APLU), and is officially designated as a Research (Very High Research Activity) and Community Engagement University by the Carnegie Foundation. The Hong group is affiliated with National Institute for Mathematical and Biological Synthesis (NIMBioS) at UTK, which offers a vibrant environment for mathematical and computational biologists with a variety of collaborative education, outreach and research programs. For large scale data analysis, the candidate will be able to leverage resources at the Advanced Computing Facility of the National Institute for Computational Sciences (NICS), co-located at the University of Tennessee and Oak Ridge National Laboratory campuses. NICS is one of the leading high-performance computing centers of excellence in the United States. The candidate will also take advantage of scientific interactions with the Bioinformatics Resource Center(BRC).
Available Subjects:
- Mathematics, statistics, computer science, computational biology, bioinformatics, or any other natural science and engineering field
Eligibility criteria:
- Proficient in at least in one of the following languages: Python, R, Julia
- Research experience with next-generation sequencing data
- Research experience with machine learning or network science
- Excellent written and oral communication skills and the ability to communicate in English to a scientific audience
Application Procedure:
- The positions are funded by NIH or NSF and are full-time assignments for 3 years with possible extensions, contingent on successful performance and continued funding.
- Applications and inquiries can be sent to Tian Hong [email protected]. Review of applications will begin immediately and continue until the positions are filled.
- Please attach the following electronic documents to the application: CV, and the names and email addresses at least three references.
