PhD in Quantitative Genetics: Genetic evaluation of cultivar mixtures integrating genomic information and soil microbiome int...

This PhD position in Quantitative Genetics focuses on the genetic evaluation of cultivar mixtures by integrating genomic data and soil microbiome interactions. The role requires advanced knowledge in quantitative genetics principles, including the analysis of genetic variation and heritability within and among plant cultivars. Expertise in genomic information processing, such as handling high-throughput genotyping data and applying genomic selection or association mapping techniques, is essential. Additionally, familiarity with soil microbiome analysis, including microbial community profiling and understanding plant-microbe interactions, is important to evaluate how microbiome factors influence cultivar performance. The candidate should be proficient in statistical genetics methods and bioinformatics tools to integrate multi-omics datasets effectively. Experience with programming languages such as R or Python for data analysis, and possibly software for genomic prediction or microbiome data analysis, will be beneficial. A strong background in experimental design and data interpretation in plant breeding or genetics research is expected. The position demands critical thinking to develop models that incorporate both genomic and microbiome data to improve cultivar mixture evaluations. This interdisciplinary role combines plant genetics, genomics, microbiology, and computational biology, requiring a solid foundation in these areas, typically demonstrated through prior research or academic training at the graduate level.