Overview

The Marcus Institute for Aging Research is actively seeking a highly qualified and motivated Post-Doctoral Research Fellow and computational biologist with a strong background in NGS-based RNA-seq at single-cell resolution as well as 10X-based single-cell multi-omics data analyses and NGS-based analytical pipelines with innovative statistical and deep-learning modeling to explain skeletal biological mechanisms underlying the observation that the response to drug therapy for osteoporosis wears off over time. The post-doc will join a Bioinformatics Core recently established via a NIH P50 Center Grant with joint effort from Harvard Medical School, Harvard Dental School, Massachusetts General Hospital, Beth Israel Deaconess Medical Center and the Marcus Institute for Aging Research, Boston, MA.

Bone biopsies from treated patients will be collected before and after treatment of osteoporosis in women who are being seen for osteoporosis at the Massachusetts General Hospital. 10X single-cell multi-omics seq, single-cell and bulk RNA-seq, and proteomics will be measured from both blood and bone biopsy samples. In addition, mice treated with the same drugs as in the clinical trials will also be conducted and bone biopsies will be collected at different time points during treatment. The same set of single-cell measurements will be conducted in bone samples collected from treated mice. Cross-species comparison analysis will also be conducted. The successful candidate will have a track record of innovative and collaborative research demonstrated through a strong training program and peer-reviewed publications.

In this vital role, the post-doc will develop and carry out analytical plans and statistical/bioinformatic analyses to study the effects of osteoporosis anabolic therapies on osteoblast progenitors as well as osteocytes in clinical and pre-clinical studies. Computational analysis on single-cell RNA-seq, bulk RNA-seq and multi-omics seq obtained from post-menopausal women and female mice treated with osteoporosis anabolic therapies (either sclerostin inhibitor or PTH) will be analyzed. Additional bioinformatic analyses will be conducted to prioritize genes regulating bone formation via existing human genetic variation association analyses; and proposed knockout mice with deeply skeletal phenotypes from collaborators. The post-doc will interact with skeletal biologists, clinicians, computational biologists, statistical geneticists, and bench scientists at Harvard Medical School, Harvard Dental School, Massachusetts General Hospital, Beth Israel Deaconess Medical Center, the Marcus Institute for Aging Research Boston University and the Broad Institute of MIT and Harvard. An ability to communicate clearly and collaborate effectively with colleagues from different disciplines will be essential.

Required Qualifications

• Doctorate degree (PhD, ScD and/or MD) in computational biology, statistical genetics, quantitative genomics, bioinformatics or relevant area
• Analytical experience with single-cell RNA-seq, single-cell multi-omics and other NGS-based seq
• Fluency in R/Python/TensorFlow analytic techniques necessary for data analysis
• Experience working with cloud computing environment and data management
• Publication track record in peer-review journals
• Experience in biomedical studies relevant to diseases being investigated including musculoskeletal diseases
• Strong interpersonal, collaborative, organizational, and presentation (oral or written) skills