Collabera is hiring: Remote Bioinformatics Analyst II (GWAS/Genetics Data) in No

What are the top 3-5 skills, experience or education required for this position:

·         Strong proficiency in R programming for bioinformatics workflows

·         Familiarity with curating/analyzing GWAS and genetics data, and transcriptomics data.

·         Ability to critically evaluate experimental design, QC and suggest improvements.

·         Experience working in HPC or cloud environment

·         Knowledge and proficiency in basic statistical concepts.

What is a nice to have (but not required) regarding skills, experience, education, or certification:

·         Experience in immunological disease area.

·         Bioinformatics/Computational Biologist (w/ focus on Genetics)

Services Overview:

·         This role involves support for the integration, organization, and analysis of large and complex multi-omics datasets, but not limited to transcriptomics, genetics, and epigenetics.

·         A vital part of this role includes ensuring the precision, quality, and comprehensiveness of our dataset repositories.

·         The successful candidate will work in synergy with cross-functional and inter-organizational teams of research scientists.

·         They will apply, refine, and expand established workflows for effective multi-omic data curation and analysis.

Key Responsibilities:

·         Curate and standardize GWAS summary statistics datasets ensuring accuracy and consistency.

·         Annotate genomic variants using established tools and databases.

·         Map SNPs to genes and determine their functional relevance.

·         Analyze transcriptomic datasets, including but not limited to bulk and single-cell RNA sequencing, to derive actionable insights.

·         Collaborate intimately with research teams to comprehend specific data requirements and applications.

·         Curate, maintain, and contribute to the project codebase.

Qualification:

·         Masters with 1+ year of experience or PhD degree in the quantitative sciences (Bioinformatics, Computer Science, Computational Genetics, Mathematics, Statistics, or a related field).

·         Proven capability in designing and implementing bioinformatics workflows and corresponding github codebase repositories.

·         in R programming and comfortable operating in a Unix/Linux and High-Performance Computing (HPC) environment.

·         Familiarity with genome-wide association studies, particularly in fine mapping and colocalization from GWAS summary data is expected.

·         Hands-on experience in curating and processing transcriptomic datasets, especially bulk and single-cell RNA-Seq, with the ability to conduct corresponding downstream analyses would be advantageous.

·         Knowledge and proficiency in basic statistical concepts, e.g. p-value, odds ratio, effect size, multiple testing correction, familiarity with Bayesian approaches employed for colocalization analysis would be advantageous.

·         Previous experience in immunological diseases or rare disease genetics is a plus.