Summary Description: An Associate Research Scientist position in human computational genomics/transcriptomics is available at Columbia University Medical Center in the Department of Neurology's Center for Translational & Computational Neuroimmunology, and the Sergievsky Center. We are looking for an enthusiastic and energetic individual to join our efforts to dissect the genetic architecture of neurodegenerative diseases, the brain's cell population structure using single cell data, and the functional consequences of human genetic and epigenomic variation in the aging brain. Specifically, the position is funded by multiple different NIH programs such as the Alzheimer's Disease (AD) Sequencing Project, and the Accelerating Medicines Partnerships for AD, to deeply investigate the genomic, epigenomic, and transcriptomic characteristics of Alzheimer's disease, aging-related cognitive decline, and other diseases of the aging brain.The candidate will play a critical role in developing and maintaining analytic pipelines as well as in managing the flow of sequence and other data through these pipelines. She or he will collaborate with experimental personnel generating the data, and the post-doctoral fellows and students analyzing the data. The candidate will receive data from the sequencing or other platform, work with the analysis team to develop an optimal quality control/quality assessment pipelines for each project, implement the planned data processing pipeline, and then process data as they arrive to generate features for downstream analysis. In addition, creative analyses of the derived data features would be encouraged. To get a sense of the data already available today, please visit the Synapse site (https://www.synapse.org/#!Synapse:syn3219045). We are analyzing whole genome sequence data on more than 10,000 subjects and have multiple levels of RNAseq and epigenomic profiles on up to 1000 brains, one of the largest set of brain samples in the world.
Minimum Qualifications: The ideal candidate should have a quantitative background (Statistics, Biostatistics, Computer Science, Computational Biology or Bioinformatics), be highly motivated to solve biological problems, and have experience analyzing large-scale and high-throughput genomics data (e.g., experience with one or more of: microarray, ChIP-Seq, ChIP-chip, genotyping, RNA-Seq data, proteomic data, or single cell data). The candidate should have a good knowledge of one scripting language for handling large-scale data (e.g., Python, Perl), and one programming language for implementing computational models and algorithms (R, Matlab, Python, C/C++). She or he will be responsible for archiving and documenting in detail each dataset that is produced. Because our work involves multiple collaborators from a wide variety of disciplines, a good balance between independence and team spirit is essential, and effective communication skills are necessary.
As a member of the National Collegiate Athletic Association (NCAA) and the Council of Ivy Group Presidents (Ivy League), it is imperative that members of the Columbia University community, in all matters related to the intercollegiate athletics program, exhibit the highest professional standards and ethical behavior with regard to adherence to NCAA, Conference, University, and Department of Intercollegiate Athletics and Physical Education rules and regulations.
Columbia University is an Equal Opportunity/Affirmative Action employer.
Internal Number: 334_65772
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