Data Analyst Research Neurology kl

Overview

A computational data analyst position is available to support the Khurana Lab and Division of Movement Disorders at Brigham and Women’s Hospital. The applicant will: i) perform analysis of high-throughput genomic and other omics data to enable novel discovery in Parkinson’s disease and related degenerative movement disorders in collaboration with computer scientists in the laboratories of Shamil Sunyaev at Harvard Medical School;

and ii) manage multi-omic and clinical data collected through the Harvard Biomarker Study (HBS), a longitudinal study of Parkinson’s disease patients and healthy controls. The role involves studying the molecular basis of synucleinopathies with the goal of identifying novel therapeutic targets, developing and utilizing multi-omic tools, and supporting both in vitro and in vivo experimental models as well as human genetic and single-cell datasets.

The Khurana Lab emphasizes collaboration among bench scientists, computer scientists, clinicians, clinician-scientists, and genetics counselors. The applicant will work closely with the multidisciplinary team to understand the genetic basis of these diseases and support precision medicine and gene-targeted therapies. Beyond genomic and omics analyses, the candidate will work with genetic study coordinators to ensure secure storage, update, and maintenance of paired genetic and clinical data from HBS 2.0 and facilitate downstream discovery.

Strong computational, organizational, and communication skills are desired. More senior candidates will be considered for Research Scientist or Senior Research Scientist positions with Research Associate appointments at Brigham and Women s Hospital and Harvard Medical School.

• Performs common/rare variant analyses including repeat and long-read sequencing analyses in collaboration with computer scientists in labs of Shamil Suyaev and Peter Park, facilitating novel gene discovery.
• Manages the HBS study database in collaboration with Mass General Brigham IT services and genetic study coordinators. This includes creating a relational database in SQL, regularly updating data tables by pulling data from third-party software platforms, backing up data, performing quality control, validation and error detection on each data point, and ensuring data security and integrity.
• Runs standard omics analysis pipelines on datasets generated in-house as well as those from collaborators via in vitro and in vivo experimental models.
• Applies and adapts existing statistical and omics tools to gain new biological insights from unique datasets.
• Works closely with bench scientists to understand and help accomplish their research goals.
• Writes and runs basic queries as needed. Assists in maintaining existing reporting systems. Contributes to presentations to key stakeholders. Works with senior analysts to design, maintain, and distribute reports.
• Learns leading practice analysis methodologies. Conducts continuous analysis of current performance and forecasts data trends.

Bachelors required. MSc or PhD in Computer Science, Mathematics in a biological science or relevant field recommended.

Data Analysis

Experience:

0-1 year preferred.

• Experience with existing bioinformatics tools or pipelines to perform standard next-generation sequencing (NGS) data analysis, including genomic, transcriptomic, epigenomic, and others.
• Developing or adapting new algorithms and pipelines to support customized data analysis.
• Strong computational genomics experience in at least two of the following NGS techniques: single-cell and bulk RNA-Seq, spatial transcriptomics, small RNA-Seq, ATAC-Seq, ChIP-Seq, WGS, WES, Hi-C.
• Experience in programming with JSON, R, Python (focus on computational biological applications).
• Experience in SQL database creation and management, writing stored procedures and queries.
• Experience in writing programs using APIs to pull data from multiple third-party software.
• Experience in Shell scripting.
• Physical server administration.
• Security compliance: HIPAA.
• Good organizational skills and attention to detail.
• Experience with common bioinformatics and genomic browsers (NCBI, Gen Bank, UCSC).
• Understanding of users of bioinformatics tools including common NGS tools (BWA, samtools, GATK).
• Ability to work in a highly collaborative and intellectually challenging environment.
• Professionalism and critical thinking with creative problem-solving abilities.
• Ability to prepare manuscripts for presentation and publication.
• Must work independently. Excellent oral and written communication skills.
• Building proficiency in statistics, data analysis, and data sets. Time management and project management skills.
• Ability to exercise sound judgment to make decisions within the scope of job responsibilities.
• Proficiency with word processing, spreadsheets, and database PC applications; strong quantitative, analytical, and technical aptitude.
• Ability to collaborate with all levels of staff and build…