Bioinformatics Data Analyst
Posted 08 Jun 2021
Brigham and Women's Hospital/Harvard Medical School
A bioinformatics data analyst position is available to support the Butovsky Lab at Brigham and Woman’s Hospital, Harvard Medical School.
The lab is looking for an applicant with experience analyzing high-throughput gene-expression data, including differential gene-expression analysis and pathway analysis. The lab studies immunologic mechanisms of neurodegenerative diseases with the goal of identifying novel therapeutic targets. It utilizes a range of genomic tools in order to analyze in vitro and in vivo experimental models and human samples. The Butovsky Lab is working in a highly collaborative environment studying multiple diseases, including Alzheimer’s disease, amyotrophic lateral sclerosis, multiple sclerosis, and eye-related diseases. The applicant would interface with the group by analyzing gene-expression data related to these disorders. Strong computational, organizational, and communication skills are desired for this position.
1. Analyze and integrate RNA-Seq from bulk RNA isolations, single-cell RNAseq, and microRNA. Perform quality control, alignment, differential analysis, pathway analysis.
2. Create visualizations and written reports.
3. Preform complete data validation and error detection; ensuring data security, integrity measures are met. Discuss with researchers to discuss results, analysis direction prior to project.
4. Maintaining an active role in research of the current trends in analysis methods, programming algorithms and using new technologies to prototype future developments
5. Contribute in the preparation of scientific methods for manuscripts detailing methods and design; Presentations of results or new tools for the department.
6. Performs all other duties/responsibilities as directed.
Bachelor's degree required. M.Sc. or Ph.D. in computer science, mathematics in a biological science, or relevant field recommended.
Skills/ Abilities/ Competencies:
- Experience with statistical analysis for differential gene expression and mapping to biologic pathways.
- Ability to apply statistical and machine-learning techniques to solve "big data" problems.
- Ability to analyze single-cell expression data.
- Good organizational skills, detail oriented.
- Experience in programing with MATLAB, R, Python and/or Java with focus on computational biological applications.
- Experience with common bioinformatics and genomic browsers [NCBI, Genbank, UCSC].
- Understanding the use of bioinformatics tools including common NGS tools [BWA, samtools, GATK].
- Ability to work in a highly collaborative and intellectually challenging environment.
- Ability to demonstrate professionalism.
- Ability to demonstrate critical thinking and creative problem-solving abilities.
- Ability to prepare manuscripts for presentation and publication.
- Must work independently.
- Excellent oral and written communication skills.