Track IV Large-Scale Population Cohorts: Subtrack 6. Human Symbiotic Microecology(J28911)

岗位职责
Introduction:
Conduct large-scale cohort studies on the microbiome, and investigate the associations between the microbiome and complex diseases.
Develop foundational models for the microbiome, explore the application of microbiome-based products, and identify potential functional units within the microbiome, such as bacteriophages and antimicrobial peptides.
Apply long-read sequencing and integrated genomic approaches to generate complete microbial genomes and high-quality metagenomic assemblies. Resolve strain-level diversity and genome structure, and improve reference resources for human microbiome research.
Build and expand human gut and oral microbial culture collections linked to curated genome databases. Integrate culturomics, taxonomic characterization, strain preservation and standardized metadata to support microbial diversity studies and functional discovery.
Identify and characterize probiotic candidates through comparative genomics, multi-omics and experimental validation. Investigate strain-specific metabolic functions, microbial metabolites and host-microbe interactions relevant to intestinal and metabolic health, while incorporating safety assessment.
Affiliated Branch(es):
Central China Branch (Wuhan)
Guangdong-Hong Kong-Macao Branch (Shenzhen)

岗位要求
(1)Preferred Background:
Microbiology, Bioinformatics, Genomics, Biotechnology, Systems Biology, Nutrition, or related life science disciplines.
(2)Core Technical Skills:
Experience in one or more relevant areas: microbial cultivation and strain characterization; long-read sequencing, genome assembly and annotation; or microbiome and multi-omics analysis using Python/R and Linux. Ability to maintain clear experimental or computational records and interpret results critically.
(3)Modeling Competency:
Ability to apply statistical methods to genomic and phenotypic data. Familiarity with genome-scale metabolic modeling, microbial interaction analysis or machine learning is advantageous, particularly for computational projects.
(4)Preferred Qualifications:
Prior research on human microbiota, microbial culture collections, comparative genomics or probiotic function. Experience linking computational predictions with experimental evidence, curating biological databases or developing reproducible analysis workflows is a plus.
(5)Personal Traits:
Scientific curiosity, research integrity and careful attention to data quality. Willingness to learn across experimental and computational disciplines, collaborate in an international team and communicate research clearly in English.