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.

Job Tags

Full time, Contract work, Remote work,

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