Job Summary
We are seeking applicants for a postdoc position that offers a unique and great opportunity of interdisciplinary training in machine learning and functional genomics. 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 state-of-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.
Required Qualifications
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.
Preferred Qualifications
We value demonstrated excellence in the following areas:
- Performing and/or analyzing functional genomics experiments
- Competence with Unix environment, R, Python, high performing cluster
- Familiarity with machine learning
- Have taken coursework in calculus, linear algebra, probability and statistics, and possess strong proficiency in mathematical thinking and abstract reasoning.
- Cellular, biochemical, molecular experimental skills
- Experience working with plant species in research settings
- Strong analytical ability and troubleshooting skills
- Excellent organization and communication skills
- Curiosity that goes across disciplinary boundaries
- Independence and leadership in research projects