Open Postdoctoral position, faculty mentor Matteo Molè

Project Description

Join a pioneering project at Stanford University to create “A Spatial Transcriptomic Atlas of Embryo-Endometrial Crosstalk During Implantation and Human Embryo Development”. This position is funded by a new collaborative grant between the laboratories of Dr. Xiaojie Qiu (Genetics & Computer Science) and Dr. Matteo Molè (Obstetrics & Gynecology).

Our goal is to explore the “black box” of early human pregnancy by mapping the precise gene activity and cell-cell interaction between the developing embryo and maternal endometrium. This work addresses a critical factor in human reproduction, as implantation failure remains a major reason for IVF treatment failure and early pregnancy loss. 

You will work at the interface of the Molè and Qiu labs as the lead experimental scientist or computational/AI scientist on this project. This is a unique opportunity to work in a cutting-edge, interdisciplinary environment, leveraging a novel in-vitro model of the human uterus and/or cutting edges machine learning techniques to make foundational discoveries in reproductive medicine. The annual salary for this full-time position starts at $76,383, dependent upon skills and previous experience. Initial appointment is 1 year with expected renewal after the first year for additional years. 

 Position Summary:

We are seeking 1-2 highly motivated Postdoctoral Scholars to lead a multifaceted project focusing on investigating fundamental mechanisms of human embryo development. This is a unique opportunity to work at the intersection of developmental biology, spatial genomics, computational biology and AI. We aim to appoint one postdoctoral scholar with strong computational skills and a second experimental postdoctoral scholar to work at the interface between the two labs to integrate experimental and computational data.

 Key Responsibilities:

• Building 3D complex endometrial models and optimizing in vitro implantation assays. 

• Culturing human embryos and generating stem cell-based embryo models. 

• Tissue sectioning for advanced spatial transcriptomic analysis.

• Leading the analysis of single-cell and spatial transcriptomics data.

• Applying and developing the analysis framework for spatiotemporal modeling. 

• Publication in top-tier journals, and apply and obtain competitive funding if interested. 

• Maintain meticulous research records and support operational/reporting responsibilities associated with clinical research.