Planet Pharma
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Target PR Range: 30-40/hr
*Depending one experience
Bioinformatician/Computational Biologist – transcriptomics focused
Services Overview:
This role involves support for the integration, organization, and analysis of multi-omics datasets, including but not limited to transcriptomics, genetics, and epigenetics. A vital part of this role includes ensuring the precision, quality, and comprehensiveness of our dataset repositories. The successful candidate will work in synergy with cross-functional and inter-organizational teams of research scientists. They will apply, refine, and expand established workflows for effective multi-omic data curation and analysis.
Qualification:
• Master's degree with 1+ years experience or an undergraduate degree with 3+ years experience in the quantitative sciences (Bioinformatics, Computer Science, Mathematics, Statistics, or a related field).
• Demonstrated experience in the analysis and integration of NGS data. Prior research experience in studying immunological diseases areas is a plus.
• Familiarity with the construction and execution of bioinformatics workflows.
• Proficiency in R programming and experience with SQL.
• Experience in curating, checking, and processing transcriptomic datasets (such as bulk and single-cell RNA-Seq) and corresponding downstream analyses.
• Knowledge and proficiency in basic statistical concepts.
• Proficiency in operating in a Unix/Linux and High-Performance Computing (HPC) environment.
Bioinformatician/Computational Biologist – transcriptomics and genetics focused
Services Overview:
This role involves support for the integration, organization, and analysis of large and complex multi-omics datasets, including but not limited to transcriptomics, genetics, and epigenetics. A vital part of this role includes ensuring the precision, quality, and comprehensiveness of our dataset repositories. The successful candidate will work in synergy with cross-functional and inter-organizational teams of research scientists. They will apply, refine, and expand established workflows for effective multi-omic data curation and analysis.
Qualification:
• Master's degree with 1+ years experience or an undergraduate degree with 3+ years experience in the quantitative sciences (Bioinformatics, Computer Science, Computational Genetics, Mathematics, Statistics, or a related field).
• Familiarity with the construction and execution of bioinformatics workflows.
• Proficiency in R programming and experience with SQL.
• Experience in curating, checking, and processing transcriptomic datasets (such as bulk and single-cell RNA-Seq) and corresponding downstream analyses.
• Experience with genome-wide association studies, particularly fine mapping and colocalization from GWAS summary data is a plus. Familiarity with rare disease genetics resources and biomedical ontologies is also a plus.
• Knowledge and proficiency in basic statistical concepts.
• Prior research experience in studying immunological diseases areas is a plus.
• Proficiency in operating in a Unix/Linux and High-Performance Computing (HPC) environment.
?*CO/NYC candidates might not be considered
Bioinformatician/Computational Biologist
Posted: 08/25/2023
2023-08-25
2024-05-17
Employment Type:
Contract
Job Category: Scientific
Job Number: 583223
Is job remote?: Yes
Country: United States
Job Description
Target PR Range: 30-40/hr
*Depending one experience
Bioinformatician/Computational Biologist – transcriptomics focused
Services Overview:
This role involves support for the integration, organization, and analysis of multi-omics datasets, including but not limited to transcriptomics, genetics, and epigenetics. A vital part of this role includes ensuring the precision, quality, and comprehensiveness of our dataset repositories. The successful candidate will work in synergy with cross-functional and inter-organizational teams of research scientists. They will apply, refine, and expand established workflows for effective multi-omic data curation and analysis.
Qualification:
• Master's degree with 1+ years experience or an undergraduate degree with 3+ years experience in the quantitative sciences (Bioinformatics, Computer Science, Mathematics, Statistics, or a related field).
• Demonstrated experience in the analysis and integration of NGS data. Prior research experience in studying immunological diseases areas is a plus.
• Familiarity with the construction and execution of bioinformatics workflows.
• Proficiency in R programming and experience with SQL.
• Experience in curating, checking, and processing transcriptomic datasets (such as bulk and single-cell RNA-Seq) and corresponding downstream analyses.
• Knowledge and proficiency in basic statistical concepts.
• Proficiency in operating in a Unix/Linux and High-Performance Computing (HPC) environment.
Bioinformatician/Computational Biologist – transcriptomics and genetics focused
Services Overview:
This role involves support for the integration, organization, and analysis of large and complex multi-omics datasets, including but not limited to transcriptomics, genetics, and epigenetics. A vital part of this role includes ensuring the precision, quality, and comprehensiveness of our dataset repositories. The successful candidate will work in synergy with cross-functional and inter-organizational teams of research scientists. They will apply, refine, and expand established workflows for effective multi-omic data curation and analysis.
Qualification:
• Master's degree with 1+ years experience or an undergraduate degree with 3+ years experience in the quantitative sciences (Bioinformatics, Computer Science, Computational Genetics, Mathematics, Statistics, or a related field).
• Familiarity with the construction and execution of bioinformatics workflows.
• Proficiency in R programming and experience with SQL.
• Experience in curating, checking, and processing transcriptomic datasets (such as bulk and single-cell RNA-Seq) and corresponding downstream analyses.
• Experience with genome-wide association studies, particularly fine mapping and colocalization from GWAS summary data is a plus. Familiarity with rare disease genetics resources and biomedical ontologies is also a plus.
• Knowledge and proficiency in basic statistical concepts.
• Prior research experience in studying immunological diseases areas is a plus.
• Proficiency in operating in a Unix/Linux and High-Performance Computing (HPC) environment.
?*CO/NYC candidates might not be considered
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