Job Descriptions
Interested candidates should send their CV and cover letter describing their background and interests to Dr. Yi-Hsiang Hsu, yihsianghsu@hsl.harvard.edu
Post-Doctoral Fellowship Opportunity at Harvard Medical School - Computational Biology
Job Title: Postdoctoral Fellow – Computational Biology in Single-Cell Multi-Omics
Location: Hinda and Arthur Marcus Institute for Aging Research and Harvard Medical School, Boston, MA Assignment Length: 3 years
Basic Qualifications: Doctoral degree (such as PhD, ScD, MD, etc.) at the time of appointment
Job Summary
We are actively seeking a highly qualified and motivated 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
Preferred 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
Post-Doctoral Fellowship Opportunity at Harvard Medical School - Statistical Genetics and Proteomics
Job Title: Postdoctoral Fellow – Statistical Genetics and Proteomics
Location: Hinda and Arthur Marcus Institute for Aging Research and Harvard Medical School, Boston, MA Assignment Length: 3 years
Basic Qualifications: Doctoral degree (such as PhD, ScD, MD, etc.) at the time of appointment
Job Summary
We are actively seeking a highly qualified and motivated statistical geneticist with a strong background in NGS-based whole genome-seq, bisulfate methylation, whole genome seq, and genome-wide association analyses with both common and rare variant association approaches. The preferred candidate will have experience with innovative statistical and deep-learning modeling to accelerate our research on aging related disorders. . The post-doc will join a Bioinformatics Core recently established via an 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.
In this vital role, the post-doc will develop and carry out analytical plans and statistical/bioinformatic analyses. The post-doc will conduct studies including: (1) performing bone tissue type specific proteomics QTL (pQTL), methylationQTL and eQTL analyses in human bone biopsies samples with existing proteomics, whole genome seq, whole genome bisulfate seq and RNA-seq data; (2) performing fine-mapping of musculoskeletal traits using whole genome sequencing data from the NHLBI TOPMed Project, UK Biobank and All of US studies; (3) performing genomic annotation to identify functional roles of associated variants and their targeted genes using in-house functional genomics and gene regulatory circuits data generated from human primary bone cell and muscle cell-specific 3D chromatin interaction data (for example, enhancer-promoter pairs); and (4) performing biological networks and systems biology analyses to study perturbation consequence of the genes associated with musculoskeletal disorders.
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, Marcus Institute for Aging Research Boston University and Broad Institute of MIT and Harvard. An ability to communicate clearly and collaborate effectively with colleagues from different disciplines will be essential.
Preferred Qualifications
Doctorate degree (PhD, ScD and/or MD) in statistical genetics, computational biology, quantitative genomics, bioinformatics or relevant area with experiences in human genetic research
Analytical experience with WGS, WES, bisulfate methylation seq and/or proteomics (LS-MS, OLINK or Somascan proteomics platforms)
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 aging related diseases
Strong interpersonal, collaborative, organizational, and presentation (oral or written) skills
Familiarity in use of large-scale omics data, such as UK Biobank, 1KG, ENCODE, Roadmap Epigenomics Project, GTEX, eQTL datasets, Hi-C and RNA-seq data as well as genomic browsers (UCSC, Ensembl, etc…) and variant annotation tools (such as VEP, ANNOVA, WGCNA, etc…)
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. We strongly encourage both women and minorities to apply.