Seeking a skilled bioinformatician who relishes the reality of sequence analysis of WGS for over 3000 subjects with Alzheimer’s:
GENOME BIOINFORMATICS OF ALZHEIMER’S
two positions available: Engineering (1) and research (2)
Position 1: Seeking a skilled bioinformatician who relishes the reality of sequence analysis of WGS for over 3000 subjects with Alzheimer’s
Please apply to whide [at] bidmc [dot] harvard [dot] edu with your cv
As part of the Cure Alzheimer’s Genome Project, the Hide laboratory at Beth Israel Deaconess Medical Center seeks a highly motivated person to join our team. As a Computational Genomics Scientist, you will be responsible for application, benchmarking and continuous improvement of our genome analysis pipeline for whole genome sequencing (WGS) of subjects afflicted with Alzheimer’s. You will manage apprehension, storage, security and delivery of whole genome sequencing data into a cloud environment such as Terra where analysis will take place. You will oversee daily operation of the pipeline and handling of custom analysis, annotation and reporting for BIDMC staff and our collaborators. You should have significant experience in DNA sequencing analysis, including evidence of familiarity with best practice approaches to alignment, variant calling, and structural variant calling. It is important that you have previous experience in cloud-based analyses, preferably at scale. Expertise in Alzheimer’s disease genetics would be ideal. You will be comfortable with statistical methods for data QC and evaluation and presentation of both production metrics and scientific results. Your excellent communication skills and successful collaboration with other members of the computational biology team as well as external collaborators and clients is really important to us. We would welcome your insights and research activity in integrating WGS into omics.
Primary responsibility for maintenance, improvement, and operation of the WGS analysis pipeline
Remaining current with and performing analysis of sequencing data using best practice workflows
Development of novel sequence analysis methods where off-the-shelf methods are inadequate
Outwards community facing interaction to support / drive best practice
Generate and track appropriate quality metrics for high throughput sequencing operations
Work with internal staff and collaborators to implement methods or prototype and benchmark customized analysis and annotation pipelines
Work with the clinical team to manage transfer of research pipelines to the clinical lab as needed
Work with the Broad Institute Terra management team to ensure optimal and efficient use of cloud facilities.
Assist, collaborate, and consult with internal/external researchers on analysis of genomic data
Interpret and present analysis results to co-workers and collaborators
Perform research and data integration leveraging the tools and data you generate
Publish results in scientific journals and give presentations at conferences when possible.
Ph.D. in bioinformatics, computational biology, genetics, computer science or similar
Experience in DNA sequencing analysis, including alignment, variant calling, structural variant calling, and interactive exploration of variant information and annotation.
Experience in population genetics and genetics of complex traits.
Proficiency in utilizing data from public resources such as Genome in a Bottle, 1000 Genomes, ExAC, and GnomAD
Proficiency in R, and one or more programming languages such as Python, Perl, Java, or C/C++, willingness to learn new programming languages
Experience working in Linux and running tasks in a cluster environment and experience in cloud environments
Experience at minimum with sufficient statistical knowledge to develop and interpret standard QC metrics for sequencing
Cloud data manipulation/analysis/processing
Experience working in teams centered around a biological question and with external collaborators
Excellent written and verbal communication skills.