An exciting opportunity has arisen for a Senior Postdoctoral Researcher to join the Ding Group at the John Innes Centre, working on cutting-edge science in the field of Cell and Developmental Biology.
About the Ding Group
Yiliang Ding’s group encompasses three sub-groups with different scientific goals:
AI sub-group (Exploration of the application of AI tools in understanding the co-transcriptional and post-transcriptional gene regulations, including RNA structure-mediated and DNA structure-mediated gene regulations).
RNA nuclear export sub-group (Exploring the RNA structure functionality in RNA export and processing).
Co-transcriptional and epigenetic regulation of FLC.
The role
Working as part of a team led by Yiliang Ding, you will lead an internationally competitive research programme within the Ding group at the John Innes Centre, focused on developing plant-specific AI approaches for understanding RNA and DNA regulation.
The role will involve building and applying RNA/DNA foundation models to identify functional sequence and structure motifs, with an initial emphasis on co-transcriptional and post-transcriptional regulatory mechanisms where RNA structure plays a central role. The post-holder will work closely with experimental researchers to ensure seamless integration of computational predictions with experimental validation and rapid publication.
The successful candidate will report to Professor Ding and lead a small computational sub-group, including the supervision of 1–3 PhD students. They will collaborate extensively with experimentalists in the Ding lab, computational partners across the Norwich Research Park (including the Earlham Institute), and international collaborators. The role also includes contributing to grant applications, representing the group at international meetings, and maintaining the group’s position at the forefront of AI-driven plant biology.
Candidates should hold a PhD in computational biology, bioinformatics, artificial intelligence, RNA biology, or a related discipline, with strong experience in AI/machine learning applied to RNA/DNA research, particularly RNA structure.
The ideal candidate
You will have a PhD (full award or expected within 6 months) or equivalent in computational biology and bioinformatics, artificial intelligence, RNA biology, or a related discipline, with strong experience in AI/machine learning applied to RNA/DNA research, particularly RNA structure.
A track record of independent research, scientific writing, and presentations is essential. Experience supervising students, preparing grant applications, and managing research activities is highly desirable. Excellent communication, organisational, and interpersonal skills, together with the ability to work independently and collaboratively in a multidisciplinary environment, are required.