Post Doc Research Associate

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

FLSA Status

Exempt