The focus of the Sampson Lab at Boston Children’s Hospital/Harvard Medical School is to discover the molecular basis of nephrotic syndrome through human genomics to inform mechanisms, treatments, and cures for this disease (http://sampsonlab.org). We integrate genomics data with other molecular and clinical datasets to discover the biological and clinical impact of the disease-associated genomic variants we discover. We also focus on using large Biobanks to empower genomic discovery for NS. Finally, we are also using new technologies and developing analytic strategies to make definitive genomic diagnoses for patients.

We now seek an intellectually curious and independent thinking post-doctoral fellow to drive forward projects in one or more of these broad research areas.

Specific projects available include:

• GWAS and blood and kidney eQTL/pQTL studies of immunosuppressive sensitive NS

• Genomic and single cell multiomic analysis of APOL1 mediated kidney disease

• Transcriptome-driven genetic diagnosis of nephrotic syndrome

• Nephrotic syndrome discovery using population- and hospital-based Biobanks

We are most interested in applicants with excellent skills in biostatistics, as well as a strong understanding of human genetics, bioinformatics, and/or genome biology. They will use both well-established and newer methods for analysis of diverse types of genomic data, including genome and exome sequencing, and bulk and single cell transcriptomics. They will drive their own projects and also support the efforts of other members of the group.

The Sampson Lab is located at Boston Children’s Hospital and is affiliated with Harvard Medical School, the Broad Institute of MIT and Harvard, and Brigham & Women’s Hospital. It is well-funded through multiple Federal grants and other resources. It is a vibrant, highly collaborative, and multidisciplinary environment made up of nephrologists, computational geneticists, biostatisticians, and epidemiologists, and bench researchers.

Responsibilities:

• Designing, troubleshooting, and analysis of diverse genomic discovery efforts using our own genomic & phenotypic data & those aggregated from publicly available resources.

• Independent thinking and decision making related to study design and analysis

• Demonstrate attention to detail and problem-solving skills.

• Excellent communication with external collaborators

• Preparation of manuscripts, grants, and presentations.

Minimum qualifications:

• PhD in biostatistics, biocomputing/bioinformatics, genetics/genomics, or a related field

• Experience in any of the following: GWAS, eQTL, single cell analysis, human genetics/genomics, variant calling, rare diseases

• Strong communication skills (writing and presenting)

• Programming experience in UNIX, R, and/or Python

• Familiarity with high-performance and/or cloud computing

• Evidence of prior publication(s) and conference/oral presentations

• Excellence in collaborating and interacting with others

Preferred qualifications:

• Working with bioinformatics analysis pipelines, code version control (e.g., git) tools and/or experience with standard bioinformatic tools (e.g., samtools, PLINK, bedtools)

• Familiarity with reproducible data science using Jupyter Notebook or RMarkdown or other

• An understanding of biological systems

Interested candidates should send a cover letter & CV to:

matthew.sampson@childrens.harvard.edu

Matt Sampson, MD MSCE ASCI

Warren E. Grupe Chair in Pediatric Nephrology, Boston Children’s Hospital

Associate Professor of Pediatrics and Medicing, Harvard Medical School

Associate Member, Broad Institute

Research Faculty, Brigham and Women’s Hospital

Full-time postdoctoral positions are available in Dongwon Lee’s laboratory. We study disease-associated genetic variants using computational approaches with a particular focus on transcriptional regulatory mechanisms. We have developed several machine-learning methods for the analysis of regulatory elements and regulatory variants (Lee et al., Nature Genetics 2015; Lee, Bioinformatics 2016; Lee et al., Genome Research 2018; Han et al., PNAS 2022). Projects will include the development of computational methods to model regulatory control of human disease by incorporating improved machine-learning/deep-learning algorithms and single-cell multi-omics data (genomic, transcriptomic, and epigenomic). There will also be ample opportunity to collaborate with clinicians and wet-lab biologists to apply our methods to clinical genetic and genomic data and to validate our computational predictions in model systems.

• The applicant should have a Ph.D. degree in computational biology, bioinformatics, bioengineering, biostatistics, computer science, or other related fields.

• Strong programming skills in Python, R, C/C++, or equivalent are required.

• Experience with Unix/Linux and working with large genetic and genomic data in a high-performance cluster computing environment is highly preferred.

• Excellent written and verbal communication skills and a willingness to write grant proposals and manuscripts are necessary.

Interested candidates should send a CV including three references, a cover letter, and representative papers (up to two) to:

dongwon.lee@childrens.harvard.edu

Dongwon Lee, PhD

Assistant Professor of Pediatrics, Division of Nephrology,

Boston Children’s Hospital, and Harvard Medical School

Manton Center Associate, The Manton Center for Orphan Disease Research