A little about us:
The Lieber Institute for Brain Development (LIBD) was established in 2010 to plot a new course in biomedical research that would change the lives of individuals affected with developmental brain disorders. We are one of the only research institutions in the world focused specifically on understanding how genes and the environment influence the way our brains develop that lead to conditions such as schizophrenia, autism, bipolar disorder and related developmental brain disorders. Through our cutting-edge research, answers are emerging and being translated into a robust pipeline of new drugs in development. And, by focusing on genes and their dynamic interplay with the environment, we are getting even closer to the “holy grail” in medical research, the discovery of strategies for primary prevention.
We are a group of dedicated, multidisciplinary and optimistic researchers, working at the cutting edge of science, utilizing state-of-the-art tools to unlock the mystery of the brain and transform the way we approach the development of new treatments, and ultimately cures. LIBD is an independent 501(c)(3) medical research institute located in the Bioscience Park on the campus of the Johns Hopkins School of Medicine and Hospital in Baltimore, MD.
A little about the team and principal investigator:
Dr. Leonardo Collado-Torres, Investigator at the Lieber Institute for Brain Development (LIBD), leads the R/Bioconductor-powered Team Data Science group that works on understanding the roots and signatures of disease (particularly psychiatric disorders) by zooming in across dimensions of gene activity. We achieve this by studying gene expression at all expression feature levels (genes, exons, exon-exon junctions, and un-annotated regions) and by using different gene expression measurement technologies (bulk RNA-seq, single cell/nuclei RNA-seq, and spatial transcriptomics) that provide finer biological resolution and localization of gene expression. This group works closely with collaborators from LIBD as well as from Johns Hopkins University (JHU) which reflects the cross-disciplinary approach and diversity in expertise needed to further advance our understanding of high throughout biology. Leonardo is also interested in outreach activities as member of the Bioconductor Community Advisory Board, the advisory board for rOpenSci’s Statistical Software Peer Review, and the board of the Community of Bioinformatics Software Developers in Mexico. In order to provide a supportive and stimulating research environment the team is involved in career planning, internal training opportunities, data science guidance sessions, the LIBD rstats club, among other initiatives.
The R/Bioconductor-powered Team Data Science group at LIBD has a Research Assistant position in genomics data science available now. This Research Assistant will have the opportunity to focus on one and participate in several of the projects the team is involved in. These projects involve several large bulk RNA-seq projects, deconvolution of bulk RNA-seq data using snRNA-seq reference data, spatial transcriptomics data from the 10x Genomics Visium platform (genomics and image processing), and integration of RNA-seq data with DNA genotype data through TWAS. They will also be involved in new projects and technologies that will help us further our understanding of psychiatric disorders.
Specific Duties and Responsibilities:
· Perform creative, rigorous and reproducible analyses on multi-omics datasets generated from the human postmortem brain samples at LIBD from technologies such as bulk RNA-seq, single cell/nuclei RNA-seq, and spatial transcriptomics.
· Utilize publicly available data such as the uniformly processed RNA-seq data from the recount3 project to enrich our findings from the LIBD datasets.
· Communicate with individuals with different expertise such as biologists, computational scientists, and biostatisticians.
· Assists in presenting research results at team meetings and scientific conferences as well as contribute to peer-reviewed publications and grant applications.
· Perform computational work on a high-performance computing environment called JHPCE (with helper tools like sgejobs), version control code with GitHub, and communicate with team members using Slack.
· Follow the JHU and LIBD policies as well as the Bioconductor project code of conduct.
· Other duties as assigned.
** If accommodations are needed due to pregnancy or a disability, please contact email@example.com
EEOC Statement: At the Lieber Institute, we are committed to a work environment of mutual respect where employment decisions are based on merit. As an equal opportunity employer, the Lieber Institute does not discriminate in employment opportunities on the basis of race, color, religion, color, sex, gender identity/expression, sexual orientation, pregnancy, marital status, age, national origin or ancestry, citizenship, disability (physical or mental), genetic information, military service, or other non-merit based factors protected by state or federal law or local ordinance, with regard to any position or employment for which the applicant or employee is qualified.
· Bachelor’s degree in computer science, computational biology, biostatistics, bioinformatics, biomedical engineering, or a related field is required.
· Previous related experience is preferred.
Special Knowledge, Skills, and Abilities:
· R/Bioconductor experience
· Strong organizational skills, excellent problem-solving skills, excellent written and verbal communication skills
· Desire to keep learning more about biology and computational methods, and ways to integrate them
· Evidence of computational skills and code version control through GitHub or similar options
· Experience using Linux and high-performance computing environments
· Understanding of statistical methods such as linear regression, ANOVA, t-Student and F distributions, p-values and false discovery rate (FDR)
· Python experience is a plus as we do have potential python-based projects with image analysis and/or deep learning methods
· Public presentation skills are a plus, and can be developed otherwise