Postdoctoral Associate

　　Baylor College of Medicine

　　Houston, TX

　　$48,432 a year

　　The postdoctoral associate will participate in a project to study the function of maternal effect genes using animal (mouse) and cell culture models. We are specifically interested in genes that encode proteins of the subcortical maternal complex of the oocyte and early embryo that are important for fertility and reproductive success. The project will involve investigating how they affect early development and reproductive outcomes via epigenetic mechanisms. The postdoc will work on an NIH- funded projects to characterize the consequences of inactivation these proteins in mice and embryonic stem cells. Experiments will involve mouse breeding, including in vitro fertilization and, embryo transfer and cross fostering of offspring, high throughput epigenomics and expression profiling, detailed placenta and embryo characterization.

　　The impact of this research will be to better understand pathways and molecules involved in early embryo development and how maternal mutations contribute to fertility and reproductive outcomes, which may ultimately lead to better diagnosis and treatment of these conditions.

　　Required:

　　PhD, MD/PhD or MD degree and a strong background in reproductive genetics.

　　Ability to work independently and take a leading role on the assigned project, under supervision and guidance of the P.I.

　　Ability to participate in supervision of less experienced lab members.

　　The following skills are highly desired for this position:

　　Experience with DNA & RNA Extraction and analysis, cell culture, cloning, transfection, PCR, including qRT-PCR, tissue dissection and preparation for histology, in situ hybridization, immunostaining, protein analysis by western blotting and immunoprecipitation, mouse colony management and breeding.

　　Experience with thorough experimental design, including sample size assessment, statistical analysis and interpretation, scientific database skills. Experience with experimental design for high-throughput sequencing-based expression and epigenomic profiling and their data analysis, which will be done with assistance of core facilities and bioinformatics collaborators.

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