Post by pepo on Jun 4, 2014 23:40:18 GMT -4
The National Human Genome Research Institute (NHGRI), a major research component of the National Institutes of Health (NIH) and the Department of Health and Human Services (DHHS), seeks to identify an outstanding Post-Doctoral Fellow for the Genomic Functional Analysis Section (GFAS) of the Translational and Functional Genomics Branch (TFGB).
The Genomic Functional Analysis Section (1) Plans and conducts research investigating functional entities in the human genome; (2) characterizes the relationship of the aforementioned elements to those in non-human organisms with respect to sequence alignment and phylogeny; (3) aims to analyze the relationship between mutations in functional elements and correlations with human genetic diseases; (4) integrates epigenomic and genomic data with transcriptomic outcomes and (5) provides genomics analysis tools to the community at large for the betterment of computational genomics as a field of study.
The computational project focuses on the analysis of large-scale data and statistical associations between the methylation of DNA and disease-causing genomic mutations. Specifically the group is working in the area of cancer genomes and mechanisms that lead to aberrant DNA methylation. Complementary analyses of these mechanisms are ongoing in the experimental wet-lab, and through next generation sequencing.
Goals of the Scientist position are to develop computational tools and pipelines for the analysis of large-scale genomic data, to address new and emerging questions in the field of epigenetics, and to provide support for team-based research projects ongoing in the lab. Individual expertise will be fostered and encouraged through travel to scientific meetings, publications in peer reviewed journals and oral presentations.
Major Responsibilities:
Lead a project on data analysis involving large-scale DNA methylation, gene expression and gene mutation data.
Develop and evaluate statistical/computational solutions to manage data flood and turn it to meaningful biological interpretations.
Develop or acquire new computational tools for data analysis
Interface and actively collaborate with other researchers, including external and academic partners
Actively participate in supporting group members research projects/ cross functional teams
Assist bench scientists via data analysis
Qualifications:
US Citizen or Resident with Ph.D. in Computational Biology, Statistics, Bioinformatics
No more than 5 years from acquiring a PhD
3+ years Working knowledge of computational programs such as Operating Systems (e.g. UNIX, LINUX, Windows); Scripting languages (e.g. Perl, Python, Bash, Tcl); Programming languages (e.g. Java, C/C++) and statistical programing (R or MatLab)
Record of high quality publications. 1st or 2nd author in reputable publications and oral presentations
Proven ability to analyze and compare genome-wide data
Experience in collecting and analyzing experimental data and use of computational tools
Thorough knowledge of research principles and techniques used in genomic research projects
Experience in programming biology-related software for data mining (e.g. genome sequences) required
Self-starter and ability to work independently with minimal supervision
Strong analytical and problem-solving skills
Ability to work under strict timelines
Excellent organizational and interpersonal communication skills
Willingness and ability to travel internationally
Highly qualified candidates will have:
Hands on experience in large-scale data analysis
Experience in statistical computing
Understanding of basic molecular biology
Understanding of what genomes are, what they do, and willingness to learn very detailed aspects of molecular processes.
Ability to manage and steer research projects
Ability to prepare manuscripts for publication in top tier journals
Three references available from immediate supervisor and professional contacts
Salary is commensurate with the candidate’s experience. DHHS and NIH are Equal Opportunity Employers.
Further information about this position is available from Dr. Laura Elnitski, Head, GFAS, TFGB, NHGRI who can be reached under the subheading “genomics, postdoctoral applicant”.
In order to proceed with your application, please send Dr. Elnitski your relevant documents by using the APPLY button by June 30th 2014. (researchgate.net)
The Genomic Functional Analysis Section (1) Plans and conducts research investigating functional entities in the human genome; (2) characterizes the relationship of the aforementioned elements to those in non-human organisms with respect to sequence alignment and phylogeny; (3) aims to analyze the relationship between mutations in functional elements and correlations with human genetic diseases; (4) integrates epigenomic and genomic data with transcriptomic outcomes and (5) provides genomics analysis tools to the community at large for the betterment of computational genomics as a field of study.
The computational project focuses on the analysis of large-scale data and statistical associations between the methylation of DNA and disease-causing genomic mutations. Specifically the group is working in the area of cancer genomes and mechanisms that lead to aberrant DNA methylation. Complementary analyses of these mechanisms are ongoing in the experimental wet-lab, and through next generation sequencing.
Goals of the Scientist position are to develop computational tools and pipelines for the analysis of large-scale genomic data, to address new and emerging questions in the field of epigenetics, and to provide support for team-based research projects ongoing in the lab. Individual expertise will be fostered and encouraged through travel to scientific meetings, publications in peer reviewed journals and oral presentations.
Major Responsibilities:
Lead a project on data analysis involving large-scale DNA methylation, gene expression and gene mutation data.
Develop and evaluate statistical/computational solutions to manage data flood and turn it to meaningful biological interpretations.
Develop or acquire new computational tools for data analysis
Interface and actively collaborate with other researchers, including external and academic partners
Actively participate in supporting group members research projects/ cross functional teams
Assist bench scientists via data analysis
Qualifications:
US Citizen or Resident with Ph.D. in Computational Biology, Statistics, Bioinformatics
No more than 5 years from acquiring a PhD
3+ years Working knowledge of computational programs such as Operating Systems (e.g. UNIX, LINUX, Windows); Scripting languages (e.g. Perl, Python, Bash, Tcl); Programming languages (e.g. Java, C/C++) and statistical programing (R or MatLab)
Record of high quality publications. 1st or 2nd author in reputable publications and oral presentations
Proven ability to analyze and compare genome-wide data
Experience in collecting and analyzing experimental data and use of computational tools
Thorough knowledge of research principles and techniques used in genomic research projects
Experience in programming biology-related software for data mining (e.g. genome sequences) required
Self-starter and ability to work independently with minimal supervision
Strong analytical and problem-solving skills
Ability to work under strict timelines
Excellent organizational and interpersonal communication skills
Willingness and ability to travel internationally
Highly qualified candidates will have:
Hands on experience in large-scale data analysis
Experience in statistical computing
Understanding of basic molecular biology
Understanding of what genomes are, what they do, and willingness to learn very detailed aspects of molecular processes.
Ability to manage and steer research projects
Ability to prepare manuscripts for publication in top tier journals
Three references available from immediate supervisor and professional contacts
Salary is commensurate with the candidate’s experience. DHHS and NIH are Equal Opportunity Employers.
Further information about this position is available from Dr. Laura Elnitski, Head, GFAS, TFGB, NHGRI who can be reached under the subheading “genomics, postdoctoral applicant”.
In order to proceed with your application, please send Dr. Elnitski your relevant documents by using the APPLY button by June 30th 2014. (researchgate.net)