Open Postdoctoral position, faculty mentor Brian Kim

Location: United States
Application Deadline: Open until filled
Published: 3 days ago

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The Kim Laboratory at Stanford University seeks a highly motivated postdoctoral research associate with a background in toxicology, molecular biology and genetics,  with strong preference for proficiency in bioinformatics and programming to analyze and present results from large genomic datasets including bulk-RNA and DNA sequencing, single-cell sequencing (RNA, ATAC), and whole genome sequencing datasets. The prospective candidate will investigate the genomic basis of coronary artery disease and related complex diseases, with emphasis on identifying mechanism and modifiers of response to known toxicants leading to vascular disease, including tobacco, vaping, and air pollution. Through the use of the gene-environment interaction .

Major focus will be on a funded project to identify the drivers of gene-environment/toxicant interaction include the integration of large-scale human genome-wide association (GWAS) with bulk and single-cell (e.g. scRNA-seq and scATAC-seq) sequening, optimization of in-vitro and in-vivo exposure protocols, and use of cutting-edge informatics to prioritize causal variants for validation using  functional genomics, including CRISPR. The overall goals of this work are to define novel disease targets and context-specific mechanisms underlying vascular diseases, ultimately to inform new treatment and prevention strategies.

The CLEAN Lab at Stanford University is seeking a highly motivated and talented Postdoctoral Scholar to join our dynamic research team. The CLEAN Lab focuses on investigating the mechanisms underlying environmental toxicant-induced cardiovascular diseases and gene-environment interactions, with a specific emphasis on identifying modifiers of response to known toxicants leading to vascular diseases such as coronary artery disease. The successful candidate will contribute to a funded project aimed at uncovering the drivers of gene-environment interactions.

*Join us in unraveling the genomic mysteries of environmental cardiovascular diseases and making a lasting impact on public health!*

Responsibilities:

1. Conduct cutting-edge research in environmental cardiovascular genomics, with a focus on identifying mechanisms and modifiers of response to toxicants such as tobacco, vaping, and air pollution.
2. Analyze and interpret large genomic datasets, including bulk-RNA and DNA sequencing, single-cell sequencing (RNA, ATAC), and whole genome sequencing datasets.
3. Actively develop and maintain a dosimetry and toxicology program and workflow for the lab for in vitro and in vivo exposure systems. 
4. Collaborate with interdisciplinary teams within the CLEAN Lab and across Stanford University.
5. Contribute to manuscript preparation and submission to peer-reviewed journals.
6. Present research findings at scientific conferences and meetings.

Required Qualifications: 

1. Ph.D. in a relevant field (e.g., toxicology, genomics, bioinformatics, molecular biology).
2. Strong background in toxicology, with experience in environmental toxicants affecting cardiovascular health.
3. Proficiency in bioinformatics and programming for the analysis of large genomic datasets.
4. Experience in analyzing bulk-RNA and DNA sequencing, single-cell sequencing (RNA, ATAC), and whole genome sequencing datasets.
5. Demonstrated ability to work independently and collaboratively within a research team.
6. Excellent communication skills and a track record of scholarly publications.

Preferred Qualifications:

1. Familiarity with gene-environment interaction studies.
2. Previous experience with dosimetry and toxicology.
3. Knowledge of statistical methods for genomics data analysis.

Required Application Materials: 

1. Curriculum vitae (CV)
2. Cover letter outlining research experience and interests
3. Contact information for three professional references
4. Representative publications (if available)

 

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.

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