Job ID: 5579
Job date: 2016-05-18
End Date:
Company : Memorial Sloan Kettering Country : Role : Research Scientist
Job date: 2016-05-18
End Date:
Company : Memorial Sloan Kettering Country : Role : Research Scientist
Job Description:
We are an expanding team of computational, clinical and research investigators working in cancer genomics with a focus in blood and childhood cancers. Our mission is to establish a fully integrated research program that coordinates basic scientific discovery, early-phase clinical trials, and drug development. As part of the center’s clinical and research investigations we are generating a wealth of genomic annotation data. To support and inform both ongoing and future research in cancer, we are building end-to-end infrastructure for large-scale data analysis, storage and mining that utilises and further develops state of the art computational tools.
We are currently seeking a Bioinformatics Data Scientist to be involved in the analysis of high-throughput cancer genomics data.
As a Bioinformatics Data Scientist you will:
Support end-to-end processing using existing tools as well as development of automated solutions for data mining, and analytics. Be involved in the annotation of genome profiling data, generate and evaluate standardized quality control metrics and work alongside research and clinical colleagues to deliver answers and drive cutting edge research in cancer genomics with a focus in leukemia and childhood cancers. Required Qualifications:
Masters in Biostatistics or bioinformatics – or related quantitative discipline. Experience in working with genome profiling data to include DNA NGS data, RNA- Seq and / or epigenetic platforms (CHIP-Seq, MBD-Seq, ATAC-seq, DNAse-seq or related platforms). Experience with next-generation analysis toolkits (PICARD, GATK, samtools, MACS, STAR, etc.) Advanced skills in Perl or Python Desired experience:
R or R shiny applications Experience in Bioinformatics software development IT process management, version control, and use case testing Experience with parallelized computing
Alternative career paths may be considered for candidates with work experience or equivalent qualifications. #LI-GS1
Additional Info:
[Click Here to Access the Original Job Post]
We are an expanding team of computational, clinical and research investigators working in cancer genomics with a focus in blood and childhood cancers. Our mission is to establish a fully integrated research program that coordinates basic scientific discovery, early-phase clinical trials, and drug development. As part of the center’s clinical and research investigations we are generating a wealth of genomic annotation data. To support and inform both ongoing and future research in cancer, we are building end-to-end infrastructure for large-scale data analysis, storage and mining that utilises and further develops state of the art computational tools.
We are currently seeking a Bioinformatics Data Scientist to be involved in the analysis of high-throughput cancer genomics data.
As a Bioinformatics Data Scientist you will:
Support end-to-end processing using existing tools as well as development of automated solutions for data mining, and analytics. Be involved in the annotation of genome profiling data, generate and evaluate standardized quality control metrics and work alongside research and clinical colleagues to deliver answers and drive cutting edge research in cancer genomics with a focus in leukemia and childhood cancers. Required Qualifications:
Masters in Biostatistics or bioinformatics – or related quantitative discipline. Experience in working with genome profiling data to include DNA NGS data, RNA- Seq and / or epigenetic platforms (CHIP-Seq, MBD-Seq, ATAC-seq, DNAse-seq or related platforms). Experience with next-generation analysis toolkits (PICARD, GATK, samtools, MACS, STAR, etc.) Advanced skills in Perl or Python Desired experience:
R or R shiny applications Experience in Bioinformatics software development IT process management, version control, and use case testing Experience with parallelized computing
Alternative career paths may be considered for candidates with work experience or equivalent qualifications. #LI-GS1
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Additional Info:
[Click Here to Access the Original Job Post]