Bioinformatics Scientist
Job ID: 25-09136
Job Title: Bioinformatics Scientist
Duration: 23 months, 40 hrs / week
Location: Cambridge, MA 02141
Required Qualifications, skills and experience:-
Minimum: Ph.D. in Genetics, Genomics, Computational Biology, or a related field.
A proven track record of over 5 years in genetic data analysis.
Fundamental understanding of statistical methods and genetic data analysis and integration (e.g., variant analysis, population genetics, genomic annotations).
Proficiency in R, Python, and Bash, with the ability to establish best practices for reproducible data analyses.
Experience with high-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).
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.
Excellent written and verbal communication skills.
Preferred Qualifications:
Experience with real-world genetic data processing and analysis.
Proficient in genetic/genomic data analysis tools and techniques.
Understanding of statistical genetics principles and methods.
Expertise in AI/ML.
Key skills:-
Proficient in genetic/genomic data analysis tools and techniques-e.g., variant analysis, population genetics, genomic annotations.
Proficiency in R, Python, and Bash.
High-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).
Responsibilities:
We are looking for a data scientist with extensive experience in genetic data analysis to contribute to our innovative research efforts.
Key Responsibilities:
Data Ingestion: Query external databases to acquire relevant genetic/genomic datasets (e.g., dbSNP, 1000 Genomes Project, gnomAD, GTEx, Ensembl, Open Targets, ClinVar).
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).
QTL Analysis: Conduct QTL analysis to identify genetic loci associated with quantitative traits, utilizing tools such as PLINK, R/qtl, or TASSEL.
Population Genetics Analysis: Analyze genetic variation across populations, including allele frequency estimation, linkage disequilibrium, and population structure analysis.
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.
Documentation: Prepare detailed documentation of analysis methods and results in a timely manner.
Job ID: 25-09136
Job Title: Bioinformatics Scientist
Duration: 23 months, 40 hrs / week
Location: Cambridge, MA 02141
Required Qualifications, skills and experience:-
Minimum: Ph.D. in Genetics, Genomics, Computational Biology, or a related field.
A proven track record of over 5 years in genetic data analysis.
Fundamental understanding of statistical methods and genetic data analysis and integration (e.g., variant analysis, population genetics, genomic annotations).
Proficiency in R, Python, and Bash, with the ability to establish best practices for reproducible data analyses.
Experience with high-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).
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.
Excellent written and verbal communication skills.
Preferred Qualifications:
Experience with real-world genetic data processing and analysis.
Proficient in genetic/genomic data analysis tools and techniques.
Understanding of statistical genetics principles and methods.
Expertise in AI/ML.
Key skills:-
Proficient in genetic/genomic data analysis tools and techniques-e.g., variant analysis, population genetics, genomic annotations.
Proficiency in R, Python, and Bash.
High-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).
Responsibilities:
We are looking for a data scientist with extensive experience in genetic data analysis to contribute to our innovative research efforts.
Key Responsibilities:
Data Ingestion: Query external databases to acquire relevant genetic/genomic datasets (e.g., dbSNP, 1000 Genomes Project, gnomAD, GTEx, Ensembl, Open Targets, ClinVar).
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).
QTL Analysis: Conduct QTL analysis to identify genetic loci associated with quantitative traits, utilizing tools such as PLINK, R/qtl, or TASSEL.
Population Genetics Analysis: Analyze genetic variation across populations, including allele frequency estimation, linkage disequilibrium, and population structure analysis.
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.
Documentation: Prepare detailed documentation of analysis methods and results in a timely manner.
Job ID: 481360137
Originally Posted on: 6/15/2025
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