1. Postdoc in Computational Genomics: This position is funded by a five-year NIH R01 grant. We will study neurodegenerative diseases using an iPSC-derived brain organoid model and generate multi-modal high-dimensional time-series data of transcriptome, proteomics, and electrophysiology of both extracellular vesicles (EVs) and the cells. Total RNAs will be measured for EVs using the latest method we developed (Chen et al. Nature Methods, 2021). Single-cell RNA-seq will also be conducted for the generated brain organoids. Meanwhile, our collaborator Dr. Luke Lee at Harvard has developed a novel high-throughput 3D mini-brain platform that will capture the organoid’s electrophysiology signals in a real-time manner (Tan, Cho, and Lee, Nature Biomedical Engineering, 2021). Gene regulatory networks associated with brain development and neurodegenerative diseases will be derived, including novel regulatory non-coding RNAs based on our recent publications (e.g., Dong et al., Nature Neuroscience, 2018). We are looking for someone with a strong interest in neurological diseases and experience in NGS data analysis and multi-omics data integration. Skills in high-dimensional and time-series data modeling and visualization are highly preferred. A background in developmental biology or neurological diseases is a plus.

2. Postdoc in Computational RNA biology: This position is funded by another five-year NIH R01 grant. Dysfunction of RNA metabolism has emerged to play crucial roles in multiple neurodegeneration diseases, including Alzheimer’s Disease (AD) and Alzheimer’s Disease related dementias (ADRD). Retrotransposon element LINE1 accounts for ~20% of the human genome with only a small subset are thought to be mobile. There are increasing interest in understanding the non-retrotransposition functions, including its role in chromatin accessibility regulation. Elevated expression of retroelement RNAs has been reported during aging and in many neurodegenerative diseases including AD/ADRD, but the molecular mechanisms of the dysregulation and functionality if not clear. We will study LINE1 RNA dysregulation in AD/ADRD in collaboration with Dr. Sun Shuying’s team at Johns Hopkins University. Functional genomics data, including LINE1 RNA expression, binding sites, chromatin state, and gene regulatory network will be analyzed in an integrative and systematic manner. We are looking for someone with a strong interest in neurological diseases and RNA biology, proven experience in functional genomics data analysis.

Other requirements of the qualification. We want you to have (1) one prior original article published as the first author; (2) a Ph. D. or equivalent doctoral degree (preferably in bioinformatics, computer science, or statistical genetics); (3) research experience in bioinformatics and analyses of genome-wide data; (4) strong quantitative skills preferably in computer science, bioinformatics, or statistics are necessary; (5) fluent programming skill in R & bash & (Python | Perl | C | C++ | MATLAB); (6) excellent written and spoken English. Candidates dedicated to succeeding in an academic research career are preferred and such career paths are available.

Apply. Please submit (1) your CV, (2) a cover letter outlining your motivation, goals, strength, and weakness, and (3) contact information for three references to Dr. Xianjun Dong (xdong@rics.bwh.harvard.edu), and cc to our administrative assistant Sherri Schwaninger at sschwaninger@bwh.harvard.edu.