Position overview

The Hormozdiari Lab at UC Davis is seeking a highly motivated and talented Postdoctoral Research Fellow to spearhead the development of advanced computational methods and next-generation AI architectures for genomics and multi-omics research, with a strong focus on advancing our understanding of human health and disease.

Our lab sits at the intersection of algorithmic computer science, machine learning, AI, and large-scale multi-omics. This role offers an exciting opportunity to build cutting-edge computational frameworks that solve fundamental biological questions and directly impact our understanding of complex human diseases.

Key research areas & projects

• Algorithmic graph genomics: Developing novel graph algorithms and AI models to leverage pangenome architectures, transforming structural variant discovery and directly advancing our understanding of complex disease mechanisms.
• Complex genomic regions & repeats: Resolving complex, highly repetitive, and previously intractable regions of the genome using long-read sequencing and T2T assemblies.
• Generative AI & machine learning for multi-omics: Leveraging and optimizing advanced architectures (e.g., Transformers, Diffusion models, and VAEs) for haplotype inference and multi-omics integration.
• Disease genotypes to phenotypes: Translating structural and sequence-level variation to understand the genetic architecture of neurodevelopmental disorders (such as Autism Spectrum Disorder) and cancer genomics.

Qualifications

Required

• Ph.D. in Computer Science, Bioinformatics, Computational Biology, Statistics, Biomedical Informatics, or a closely related quantitative field.
• Strong background in algorithm design, machine learning, and deep learning frameworks.
• Proficiency in Python and high-performance computing environments.
• Demonstrated proficiency in leading deep learning frameworks, including PyTorch, TensorFlow, or JAX.
• Experience handling large-scale genomic datasets (e.g., WGS, long-read sequencing, RNA-seq, and/or single-cell data).
• A strong track record of first-author publications or high-impact conference proceedings (e.g., RECOMB, ISMB, NeurIPS, ICML).

Preferred

• Experience with pangenomics tools and workflows.
• Familiarity with probabilistic modeling or generative AI architectures.

What we offer

• Cutting-edge research: Work with state-of-the-art computational resources and unique, large-scale clinical and cohort datasets.
• Mentorship & career development: Dedicated support for transitioning to independent academic positions (including NIH K99/R00 or equivalent grants) or industry leadership roles.
• Collaborative environment: A vibrant, interdisciplinary research ecosystem at UC Davis, closely connected to world-class genomics and clinical research networks.
• Location: Enjoy the high quality of life in Northern California, with close proximity to Sacramento, the San Francisco Bay Area, and Lake Tahoe.