<p>Bioinformatics Scientist Job ID: 25-09136</p> <p>Job Title: Bioinformatics Scientist</p> <p>Duration: 23 months, 40 hrs / week</p> <p>Location: Cambridge, MA 02141</p> <p>Required Qualifications, skills and experience:-</p> <ul> <li>Minimum: Ph.D. in Genetics, Genomics, Computational Biology, or a related field. </li><li>A proven track record of over 5 years in genetic data analysis. </li><li>Fundamental understanding of statistical methods and genetic data analysis and integration (e.g., variant analysis, population genetics, genomic annotations). </li><li>Proficiency in R, Python, and Bash, with the ability to establish best practices for reproducible data analyses. </li><li>Experience with high-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets). </li><li>A collaborative and self-motivated individual with a strong work ethic, capable of managing multiple objectives in a dynamic environment and adapting to changing priorities. </li><li>Excellent written and verbal communication skills. </li></ul> <p>Preferred Qualifications:</p> <ul> <li>Experience with real-world genetic data processing and analysis. </li><li>Proficient in genetic/genomic data analysis tools and techniques. </li><li>Understanding of statistical genetics principles and methods. </li><li>Expertise in AI/ML. </li></ul> <p>Key skills:-</p> <ul> <li>Proficient in genetic/genomic data analysis tools and techniques-e.g., variant analysis, population genetics, genomic annotations. </li><li>Proficiency in R, Python, and Bash. </li><li>High-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets). </li></ul> <p>Responsibilities:</p> <p>We are looking for a data scientist with extensive experience in genetic data analysis to contribute to our innovative research efforts.</p> <p>Key Responsibilities:</p> <ul> <li>Data Ingestion: Query external databases to acquire relevant genetic/genomic datasets (e.g., dbSNP, 1000 Genomes Project, gnomAD, GTEx, Ensembl, Open Targets, ClinVar). </li><li>Genetic/Genomic Data Analysis: Perform quality control (QC) and analysis of genetic/genomic data, including genotype imputation from array data, variant calling and annotation using state-of-the-art methods (e.g., IMPUTE, Minimac, Eagle, BEAGLE, GATK, bcftools, samtools, ANNOVAR). </li><li>QTL Analysis: Conduct QTL analysis to identify genetic loci associated with quantitative traits, utilizing tools such as PLINK, R/qtl, or TASSEL. </li><li>Population Genetics Analysis: Analyze genetic variation across populations, including allele frequency estimation, linkage disequilibrium, and population structure analysis. </li><li>Data Integration: Integrate genetic datasets with other omics data, including genomic, epigenomic, transcriptomic and proteomic data, to provide comprehensive insights into gene function and regulation. </li><li>Documentation: Prepare detailed documentation of analysis methods and results in a timely manner. </li><li>Job details </li><li></li></ul>