Thank you for your interest in our job posting! We're thrilled to see your enthusiasm and would love to explore this opportunity with you further.

To dive deeper into what this role can offer, feel free to reach out to me directly. You can connect with me, Chitrank Rastogi, on LinkedIn (https://www.linkedin.com/in/chitrank-rastogi-55119a102/) for a professional introduction.

If you prefer, you can also email me your updated resume at chitrank.rastogi@collabera.com, or simply give me a call at (425) 523-1648. I'd be happy to discuss how your skills and experiences align with our needs at your earliest convenience.

Pay Range - $35 to $40/hr. (negotiable)

Job Description:
Job Roles & Responsibilities:

Top 6 required skills

• Experience with genome-wide association studies, particularly fine mapping and colocalization from GWAS summary data is a plus. Familiarity with rare disease genetics resources and biomedical ontologies is also a plus.
• Ability to critically evaluate experimental design, QC and suggest improvements.
• Strong proficiency in R and/or Python programming for bioinformatics workflows
• Experience working in HPC and cloud environment
• MS+2 or PhD in the quantitative sciences (Bioinformatics, Computer Science, Computational Genetics, Mathematics, Statistics, or a related field).
• Experience with code reproducibility, e.g. managing github repositories
• We are seeking a motivated Bioinformatics Scientist to join our cross-function team and support target identification and evaluation efforts.
• The successful candidate will work in synergy with cross-functional and inter-organizational teams of research scientists to apply, refine, and expand established workflows for effective multi-omic data curation and analysis.
• This role will have a heavy emphasis on the curation and analysis of genetics data.
  
  

Qualification:

• Master's degree with 2+ years' experience or PhD in the quantitative sciences (Bioinformatics, Computer Science, Computational Genetics, Mathematics, Statistics, or a related field).
• Experience with genome-wide association studies, particularly fine mapping and QTL colocalization from GWAS summary data is a plus. Familiarity with methods to prioritize genes per GWAS locus given multiuple lines of evidence is a plus.
• Familiarity with rare disease genetics resources and biomedical ontologies is also a plus.
• Demonstrated experience in the analysis and integration of NGS data.
• Familiarity with the construction and execution of bioinformatics workflows.
• Strong proficiency in R and/or Python programming for bioinformatics workflows.
• Knowledge and proficiency in basic statistical concepts.
• Proficiency in operating in a Unix/Linux and High-Performance Computing (HPC) environment.
• Experience with code reproducibility, e.g. managing github repositories.
• Prior research experience in studying immunological diseases areas is a plus.
• Experience with Nextflow is a plus.