Job Description

Job Title: Bioinformatics Scientist - III (Senior) Location: 320 Bent St, 4th Floor, Cambridge, MA 02141 Duration: 23-Month Contract Pay Rate: $90-100/hr Work Arrangement: Onsite Only - No remote or hybrid options available Position Overview: The Precision Genetics group within the Data and Genome Sciences Department is seeking a highly experienced Bioinformatics Scientist (Senior Level) to join our Computational Precision Genetics team . This role is ideal for a Ph.D.-level scientist with deep expertise in genetic and genomic data analysis, high-performance computing, and cloud technologies. You will play a critical role in advancing our understanding of complex diseases through computational genetics and integrated omics research. Key Responsibilities: Data Acquisition: Query and acquire genetic/genomic datasets from public databases such as dbSNP, 1000 Genomes Project, gnomAD, GTEx, Ensembl, Open Targets, and ClinVar. Genomic Analysis: Execute QC and advanced analysis of large-scale genetic data, including genotype imputation, variant calling, and annotation using tools such as IMPUTE, Minimac, Eagle, BEAGLE, GATK, bcftools, samtools, and ANNOVAR. QTL Analysis: Identify quantitative trait loci using software like PLINK, R/qtl, or TASSEL. Population Genetics: Conduct studies on allele frequency, linkage disequilibrium, and population structure. Omics Integration: Merge genetic data with transcriptomic, proteomic, and epigenomic data to generate biological insights. Documentation: Maintain comprehensive documentation of analysis pipelines, methodologies, and outcomes for internal review and publication. Required Qualifications: ~ Ph.D. in Genetics, Genomics, Computational Biology, Bioinformatics, or a related field. ~5+ years of experience conducting advanced genetic data analysis. ~ In-depth knowledge of population genetics, variant analysis, and genomic annotation. ~ Proficiency in R, Python, and Bash , with an emphasis on reproducible scientific computing practices. ~ Hands-on experience with HPC environments and AWS Cloud services (e.g., IAM, S3). ~ Strong organizational, analytical, and communication skills. ~ Proven ability to manage multiple complex objectives in a fast-paced, research-driven environment. Preferred Qualifications: Experience processing and analyzing real-world genetic datasets . Advanced expertise in AI/ML techniques applied to biological data. Deep understanding of statistical genetics principles and methods . Familiarity with genomic databases and ontologies.

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