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Job Summary

Our research focusses on understanding the role of genetic variation in the biology of neurodegenerative diseases, particularly Alzheimer's Disease. The lab is involved in several multi-institutional studies of genetics of AD including the Alzheimer's Disease Sequencing Project (ADSP). We are applying computational pipelines to characterize structural variation in large scale sequencing data for gene discovery in Alzheimer's Disease. A major focus of the lab is on multi-omics integration of genetic, transcriptomic, proteomic, metabolomics data for gene and pathway discovery in multiple cohorts including the EFIGA (Caribbean-Hispanic families) and WHICAP (Washington Heights and Inwood Columbia Aging Project). We are looking for a motivated associate research scientist with research experience to work on large-scale whole genome sequencing and multi-omics data in Alzheimer's Disease. The candidate will apply existing and novel pipelines to call structural variation in AD and test association of those variants with clinical and pathological Alzheimer's Disease. The candidate will perform multi-omics integration, quantitative trait loci (QTL) testing and network and pathway analysis.

Responsibilities

• Ideal candidate will closely interact with the PIs in the department to perform integrated multi-omics, statistical and bioinformatics analysis to identify genes and understand disease mechanisms in Alzheimer's disease and related disorders.
• The candidate will apply pipelines to call structural variation from whole genome data. Variation types include large insertions, deletions, translocations, copy number variations and short tandem repeats.
• The candidate will work on high-dimensional multi-omics data sets, including WGS, WES, RNA-seq, metabolomics and proteomics from predominantly minority populations.
• Identify and implement pipelines to process multi-omics datasets and develop robust and reproducible code/algorithms.
• Perform statistical analysis of the omics data and intermediate molecular phenotypes in family-based and case-control or cohort study set-up to identify association with disease.
• Publish and present novel research findings in academic journals and scientific meetings
• Foster collaboration with scientists with complementary interests and skills within and outside the department

• Work independently and take lead on projects and scientific proposals of particular interest to the applicant.

We are committed to provide a fertile and productive environment where the postdoctoral candidate can acquire a diverse skillset for future endeavors either in the industry or the academia and maintain a healthy work-life balance while doing cutting-edge science.

Qualifications

• PhD in Computational Biology, Bioinformatics, Biostatistics/Statistics, Genetic Epidemiology or other relevant computational disciplines (for example:-Biomedical Informatics)
• Proficient in shell scripting and programming proficiency in R, Python, C, C , or Java on UNIX/Linux environments, particularly with large data files in various formats
• Experience in analysis of human sequence data using bioinformatics tools (e.g., SAMtools, GATK, Picard, STAR, RSEM) and omics databases (Ensembl, 1000 Genomes, GnomAD, GTex, HapMap, ENCODE etc)
• Working knowledge of statistical genetics will be a plus
• Ability to analyze data on the cloud (AWS, Google or Azure) will be a plus
• Excellent written and verbal communication

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Equal Opportunity Employer / Disability / Veteran

Columbia University is committed to the hiring of qualified local residents.

Minimum Salary: 31200.00 Maximum Salary: 31200.00 Salary Unit: Yearly