Post Doctoral Scholar - Michelmore Lab

Position overview Salary range: The posted UC salary scales set the minimum pay determined by rank and/or step at appointment. The salary range for this position is $71,491-$85,736 Application Window Open date: August 19, 2026 Next review date: Friday, Sep 18, 2026 at 11:59pm (Pacific Time) Apply by this date to ensure full consideration by the committee. Final date: Friday, Sep 18, 2026 at 11:59pm (Pacific Time) Applications will continue to be accepted until this date. Position description Postdoctoral Scholar in AI and Foundation Models for Plant Genomics The UC Davis Genome Center is recruiting a Postdoctoral Scholar to work on a collaboration between the laboratories of Richard Michelmore (Plant Sciences), Xin Liu (Computer Science), and Christine Diepenbrock (Plant Sciences). This project will develop one of the first crop-specific multimodal foundation models integrating more than 100 telomere-to-telomere lettuce genomes, population-scale genomic variation, transcriptomics, and extensive phenotypic datasets to predict the consequences of allelic variation, genome editing, and genotype-by-environment interactions. The focus of this work will be on the fine-tuning, evaluation, and multi-faceted deployment of a foundation model for lettuce. An existing DNA foundation model architecture will be leveraged while also incorporating advances due to the rapid evolution of the DNA and other -omic foundation model space. The extensive existing data sets will be leveraged for training, evaluation, validation, and use cases. The project emphasizes reproducible research and open-source software development. The successful candidate will have opportunities to publish both methodological advances in AI and biological discoveries enabled by the models. Responsibilities: Fine-tune a pretrained foundation model using lettuce genome data with applications in crop improvement. Implement appropriate strategies to optimize model performance and benchmark and compare models. Collaborate closely with other project team members who have expertise in lettuce genomic resources, remote sensing, plant physiology, and development to 1) curate training data, including multi-omic and phenotypic data; and 2) generate hypotheses for model training. Supervise undergraduate researchers with training in machine learning. Publish findings in machine learning and computational biology journals. Qualifications Basic qualifications Ph.D. in Computer Science, Computational Biology, or a related field Experience programming in Python Demonstrated experience developing, training, or adapting deep learning models An interest and willingness to learn about genome biology, gene function, and regulatory circuits Willingness to collaborate in multi-disciplinary teams Evidence of research productivity through publications in machine learning, computational biology, genomics, or related areas Preferred qualifications Experience applying machine learning to biological or scientific datasets Experience in training or fine-tuning LLMs Experience with multimodal learning involving sequence, image, and tabular data Experience with model interpretability, representation learning, or variant effect prediction Experience or interest in supervising undergraduate researchers Application Requirements Document requirements: Curriculum Vitae - Your most recently updated C.V. 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Federal, state, or local government directives may impose additional requirements. Job location Davis, CA #J-18808-Ljbffr University of California - Davis