Postdoctoral Associate - Chen Lab

Description & Requirements

• The Chen Lab at the Broad Institute of MIT and Harvard and Harvard University is seeking a highly motivated postdoctoral fellow to develop and apply new technologies for understanding cellular states, tissue organization, and disease mechanisms in vivo.
• Our lab builds experimental and computational platforms to measure and perturb biology across space and time. Current areas of interest include spatial genomics, temporal recording of cell states, in vivo functional genomics, protein localization and delivery, tumor microenvironments, tissue regeneration, somatic variation, and AI-enabled models of cell and tissue biology. We are especially interested in candidates who want to develop new technologies and use them to answer fundamental biological questions.
• The postdoctoral associate will lead an independent research project aligned with the lab’s broader mission. Possible project areas include:
• · Developing new spatial or temporal genomics technologies to measure cell states, lineage, epigenetic state, or molecular history in intact tissues.
• · Applying Slide-seq, Slide-tags, TimeVault, or related platforms to study cancer, regeneration, aging, brain disease, or immune responses.
• · Building pooled in vivo perturbation systems to identify regulators of tissue repair, cell fate, tumor progression, or therapeutic response.
• · Engineering proteins, receptors, delivery systems, or subcellular localization tools to control biological function in cells and tissues.
• · Developing computational or machine learning approaches to integrate spatial, temporal, single-cell, perturbational, and imaging data.
• We welcome candidates from diverse scientific backgrounds, including molecular biology, genomics, bioengineering, immunology, cancer biology, neuroscience, developmental biology, computational biology, machine learning, chemistry, biophysics, or related fields.
• Prior experience with single-cell or spatial genomics, high-throughput screening, animal models, imaging, protein engineering, sequencing technologies, or computational analysis is helpful but not required. More important is creativity, scientific independence, rigor, and enthusiasm for developing new approaches to biological problems.
• Responsibilities will include designing and leading research projects, developing and optimizing experimental or computational methods, analyzing and interpreting data, preparing manuscripts and presentations, collaborating with other lab members and external partners, and contributing to a supportive and intellectually engaged lab environment.