Tin Nguyen’s Bioinformatic Lab
Auburn University
Department of Computer Science and Engineering (CSSE)

Multiple Ph.D. positions are available in the Bioinformatics Lab at Auburn University, starting from Spring 2024 until all positions are filled. Auburn Engineering has its brand recognition and is ranked no. 31 among Best Engineering schools in the USA. The university is known for its successful graduated students, such as Apple CEO Tim Cook, NASA Astronaut Jim Voss, Wikipedia Founder Jimmy Wales, Oscar Winner Octavia Spencer, three-time Olympic Gold-Medalist Rowdy Gaines, etc.

These positions are fully supported by Dr. Tin Nguyen’s federal grants from NASA, NIH NCI, NIGMS, NSF, and USDA. Admitted Ph.D. students to the PhD program in Computer Science will develop novel algorithms and software to solve contemporary problems in cancer and data science and artificial intelligence that can be applied in cancer, healthcare, agriculture, and space biology. This is a great opportunity to learn about state-of-the-art, large-scale data that are generated from modern instruments and develop novel methods for their analysis and interpretation. Students will learn to develop novel techniques in machine learning and bioinformatics, including but not limited to deep learning, large language models (LLM), and other techniques applied to big data analytics of patient and molecular data (single-cell, spatial transcriptome, DNA methylation, multi-omics, genome-wide association, etc.).

More details can be found at: https://tinnguyen-lab.com/home/hiring. Feel free to contact Prof. Nguyen (tinn@auburn.edu) and his student Phi Hung Bya – Alumni from the Faculty of Information Systems at UIT (pzb0047@auburn.edu) if you have any questions.

RESEARCH TOPICS

The topics of the research include, but are not limited to:

• Bioinformatics, computational biology, and systems biology
• RNA sequencing, single-cell data, spatial transcriptomics, multi-omics integration
• Pathway analysis, space biology
• Large language models, natural language processing, and artificial intelligence
• Machine learning and deep learning
• Quantum computing

More details about the lab can be found at: https://tinnguyen-lab.com/home/