Jing Gao

Home

Research

Teaching

Award

Group

Purdue ECE

Purdue

We are seeking applicants for a postdoc position that offers a unique and great opportunity of interdisciplinary training in machine learning and functional genomics.


This position is funded by the initiative of the Institute for Physical Artificial Intelligence at Purdue University to support postdocs whose innovative projects in artificial intelligence have the ability to make tangible impact on real-world problems. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning techniques including deep neural networks and large language models (such as GPTs), with stateof- the-art functional genomics approaches, including crop genomics, genome editing, and single cell multiomics, to identify and characterize novel transcriptional regulatory mechanisms that control traits of agronomic importance. This project thus offers a unique opportunity to train a future leader in combining the strengths of modern biotechnology and computational tools to address essential questions in life sciences including plant biology and crop sciences.


The postdoc will partner with two advisors, who are from different disciplines and have established collaborations, to apply artificial intelligence to improve agriculture sustainability and productivity:

Prof. Ying Li's research program aims to advance the basic understanding of genome-wide regulatory mechanisms controlling important crop physiological traits, with the goal of providing a knowledgebase for modern crop breeding and engineering efforts to improve agricultural productivity and crop resilience. Dr. Li's research methodology is interdisciplinary and integrates functional genomics, systems biology, machine learning, biochemistry, epigenetics, genetics, and plant physiology, using multiple experimental systems ranging from the model plant Arabidopsis, horticultural crops (petunia, tomato, bean, and grape), to row crops (maize). Dr. Li has become an internationally recognized expert in chromatin regulation of plant metabolism, as evidenced by publications in high-ranking scientific journals including Science, PNAS, and New phytologist and multiple million dollars support from various federal agencies. The Li lab is located within the College of Agriculture, one of the world's leading colleges of agricultural, food, life, and natural resource sciences. Purdue Agriculture is ranked #3 in the U.S. and #5 in the world according to the 2023 QS World University Rankings.

Dr. Li is dedicated to helping all her lab members to reach their full potential. She starts with developing an understanding of the strengths and goals of each lab member and works with them to achieve these goals. The success of Dr. Li's mentoring is evidenced by the many awards won by the members in the Li Lab, multiple publications authored by Li lab members, and the growth of Li lab academic tree by placing mentees into prestigious graduate programs (Yale, Washington University in St. Louis, and Purdue), biotech industry, as well as tenure track faculty position.

Prof. Jing Gao's research is in the general area of data and information analysis with a focus on data mining and machine learning. In particular, she is interested in information veracity analysis, multisource data analysis, knowledge graphs, text mining, generative AI, data and model efficiency, fairness and interpretation, transfer learning, federated learning, crowdsourcing, data stream mining, and anomaly detection. She is also interested in various data mining applications in healthcare, social science, criminal justice, biology, transportation, and education. She has published 1 book, 3 book chapters, and nearly 200 papers in prestigious scientific venues, including KDD, SIGMOD, VLDB, NIPS, ICML, AAAI, IJCAI, EMNLP, WWW, WSDM, CIKM, SDM, ICDM, ICDE, ECML/PKDD, and TKDE. Dr. Gao has a strong track record of mentoring students. The PhD students who graduated from her lab have joined Pennsylvania State University, Iowa State University, University of Georgia as faculty, Google Research, Alibaba DAMO Academy, Tencent AI Lab, J.D. Research as research scientists, and Google, LinkedIn as software engineers.

Dr. Gao's program is with Purdue Engineering College and ECE School. Purdue University hosts one of the best Engineering Colleges in US. Its Engineering College is ranked #4 by U.S. News & World Report. The ECE School is the largest academic unit at Purdue Engineering College and also one of the largest ECE programs in the country. Purdue ECE has over 120 faculty members, including 7 US National Academy of Engineering members, 42 IEEE Fellows, and a former IEEE president. In U.S. News & World Report, Purdue ECE's Electrical Engineering program is ranked #8 and its Computer Engineering program is ranked #10.


The funded postdoc will be full-time staff and receive an annual salary of $70,000 and benefits. Participating postdocs will also receive $2,500 for professional development (e.g. attending conferences or workshops) and $50,000 to support their research. The position is under yearly renewable contract, and the total funding is for two years and possible to be extended for the 3rd year.


PhD degree in genetics, genomics, biology, plant sciences, computer science, statistics or in any related field. Plant molecular biologists with prior experience in molecular genomics and are interested in expanding skillset into machine learning, as well as computational scientists who are looking to develop in-depth biological experimental skills, are encouraged to apply.


We value demonstrated excellence in the following areas:
This position is available in September 2024. Applications should be emailed to lilabpurdue@gmail.com. . Please include a cover letter, an updated CV with skills and previous education/research experience/publications, and the contacts of three references. Applications will be reviewed on a rolling basis until the position is filled.