Planet Pharma
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Bioinformatics Scientist - III (Senior)
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Planet Pharma 1 day ago Be among the first 25 applicants Job Description
Target Pay Rate: 80-100.56/hr
salary will be commensurate with experience The Precision Genetics group within the Data and Genome Sciences Department is seeking a skilled Contractor to join our Computational Precision Genetics team. 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.
Qualifications:
Required Qualifications, skills and experience: Ph.D. in Genetics, Genomics, Computational Biology, or a related field. Over 5 years of proven experience in genetic data analysis. Fundamental understanding of statistical methods and genetic data analysis and integration. 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). Collaborative, self-motivated, with a strong work ethic, capable of managing multiple objectives and adapting to changing priorities. Excellent written and verbal communication skills.
Preferred Qualifications: Experience with real-world genetic data processing and analysis. Proficiency in genetic/genomic data analysis tools and techniques. Understanding of statistical genetics principles and methods. Expertise in AI/ML.
Note: Onsite role at Cambridge, MA. Do not submit candidates seeking remote work. Candidates should have at least a Ph.D.; BS/MS candidates are not suitable.
Additional Information:
Seniority level: Not Applicable Employment type: Full-time Job function: Research, Analyst, and Information Technology Industry: Staffing and Recruiting
Referrals increase your chances of interviewing at Planet Pharma by 2x. Set job alerts for related roles: Sr. Bioinformatics Scientist AI/ML for Multimodal Precision Medicine Part-Time Lecturer, Bioinformatics (Boston) Data Processing Systems Analyst (Network Operations) Senior Data Analyst - GIS, Mapping and Analytics (Hybrid)
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Bioinformatics Scientist - III (Senior)
role at
Planet Pharma 1 day ago Be among the first 25 applicants Job Description
Target Pay Rate: 80-100.56/hr
salary will be commensurate with experience The Precision Genetics group within the Data and Genome Sciences Department is seeking a skilled Contractor to join our Computational Precision Genetics team. 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.
Qualifications:
Required Qualifications, skills and experience: Ph.D. in Genetics, Genomics, Computational Biology, or a related field. Over 5 years of proven experience in genetic data analysis. Fundamental understanding of statistical methods and genetic data analysis and integration. 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). Collaborative, self-motivated, with a strong work ethic, capable of managing multiple objectives and adapting to changing priorities. Excellent written and verbal communication skills.
Preferred Qualifications: Experience with real-world genetic data processing and analysis. Proficiency in genetic/genomic data analysis tools and techniques. Understanding of statistical genetics principles and methods. Expertise in AI/ML.
Note: Onsite role at Cambridge, MA. Do not submit candidates seeking remote work. Candidates should have at least a Ph.D.; BS/MS candidates are not suitable.
Additional Information:
Seniority level: Not Applicable Employment type: Full-time Job function: Research, Analyst, and Information Technology Industry: Staffing and Recruiting
Referrals increase your chances of interviewing at Planet Pharma by 2x. Set job alerts for related roles: Sr. Bioinformatics Scientist AI/ML for Multimodal Precision Medicine Part-Time Lecturer, Bioinformatics (Boston) Data Processing Systems Analyst (Network Operations) Senior Data Analyst - GIS, Mapping and Analytics (Hybrid)
#J-18808-Ljbffr