The Project Associate – I will be an integral member of the research team and will contribute to various aspects of the project— from data processing and variant discovery to bioinformatics analysis and field-based validation activities. This position offers a unique opportunity to engage with cutting-edge genomic research, collaborate with experienced scientists, and make a tangible impact on rice improvement efforts across South Asia. The role is well-suited for early-career professionals with a strong foundation in genetics, molecular biology, or bioinformatics, who are eager to apply their skills in a dynamic research environment with real world agricultural applications.
Responsibilities
Support the development of a mid-density genotyping panel (HaploPanel) to accelerate rice breeding through haplotype-based genomic selection.
Analyze whole genome resequencing (WGRS) data to identify key genetic variants and haplotypes associated with important agronomic traits in rice.
Assist in validating the HaploPanel by correlating phenotypic and genotypic data across diverse rice populations and breeding lines.
Contribute to the design, optimization, and application of molecular tools for trait mapping, diversity assessment, and selection strategies.
Collaborate with multidisciplinary teams to implement genomic technologies aimed at improving the efficiency and precision of rice improvement programs.
Supervise and mentor a team of researchers and support staff .
Represent IRRI to a wide audience by presenting at conferences/meetings .
Participate/contribute to visits, meetings, workshops, and any such events at ISAH and outside.
Lead and support fund generation activities by contributing to proposal writing and creating new opportunities .
Any other tasks as assigned by Supervisor.
Requirements:
M.Sc in Biology (or) equivalent degree with minimum 55% marks or
equivalent grade.
A provisional degree at the time of joining is acceptable.
Experience in molecular breeding in rice.
Publication record in peer reviewed journals.
Candidates have experience in Python and R programming languages, analyzing next generation sequencing data, and knowledge of meiosis mechanisms.
