Job Description:
The Division of Nephrology at Columbia University seeks highly motivated, independent but team-oriented post-doctoral research fellows with experience in the bioinformatic and statistical analysis of human GWAS and Next Generation Sequencing data. The work will broadly involve human genetic investigations of autoimmune forms of kidney disease, and is directly relevant to clinical medicine, as well as the National Precision Medicine Initiative (PMI). The applicant will be involved in the analysis of human GWAS and NextGen sequence data (exomes, whole genomes, bulk and single cell RNA-seq, CHIP-seq etc.). Requires a PhD degree in biostatistics, statistical genetics, bioinformatics, computational biology, human genetics or in similar field of study. Strong programming skills in Unix shell scripting and R, Perl, Python or similar. Experience in GWAS and NGS data analysis, exposure to exome and RNA-seq data, prior experience with a molecular biology and nucleic acid research is a major plus. Familiarity with the tools for network analysis and genome/transcriptome/epigenome interpretation. Familiarity with the statistical principles and methods relevant to computational genomics. Exposure to disease association studies, population genetics and/or functional genomics. Must be collaborative and able to work in a fast-paced academic environment. Strong creative thinking and problem solving skills. Team oriented with excellent written and verbal communication skills.
Additional Info:
For more information, please contact Dr. Krzysztof Kiryluk: kk473@columbia.edu Columbia University is an Equal Opportunity/Affirmative Action employer.[Click Here to Access the Original Job Post]
The Division of Nephrology at Columbia University seeks highly motivated, independent but team-oriented post-doctoral research fellows with experience in the bioinformatic and statistical analysis of human GWAS and Next Generation Sequencing data. The work will broadly involve human genetic investigations of autoimmune forms of kidney disease, and is directly relevant to clinical medicine, as well as the National Precision Medicine Initiative (PMI). The applicant will be involved in the analysis of human GWAS and NextGen sequence data (exomes, whole genomes, bulk and single cell RNA-seq, CHIP-seq etc.). Requires a PhD degree in biostatistics, statistical genetics, bioinformatics, computational biology, human genetics or in similar field of study. Strong programming skills in Unix shell scripting and R, Perl, Python or similar. Experience in GWAS and NGS data analysis, exposure to exome and RNA-seq data, prior experience with a molecular biology and nucleic acid research is a major plus. Familiarity with the tools for network analysis and genome/transcriptome/epigenome interpretation. Familiarity with the statistical principles and methods relevant to computational genomics. Exposure to disease association studies, population genetics and/or functional genomics. Must be collaborative and able to work in a fast-paced academic environment. Strong creative thinking and problem solving skills. Team oriented with excellent written and verbal communication skills.
Requeriments :
Skills :
- Bioinformatics
- genomic
- Lunix/Unix
- molecular biology
- Next Generation Sequencing
- Population Genetics
- Programing in Python
- Programing Skills
- Programming in PERL
- Programming in R
- RNA-seq
- Shell scripting
- Statistics
Areas :
Additional Info:
For more information, please contact Dr. Krzysztof Kiryluk: kk473@columbia.edu Columbia University is an Equal Opportunity/Affirmative Action employer.[Click Here to Access the Original Job Post]