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Title: Research Computer Specialist
(Department of Pediatric Nephrology. In close collaboration with the Center for Statistical Genetics, Department of Computational Medicine and Bioinformatics, and Department of Adult Nephrology)
Job Summary
We are seeking a highly skilled analyst/programmer interested in working at the intersection of cutting-edge genomics and systems biology of kidney disease. The applicant will make original contributions to a diverse set of scientific projects that seek to understand the molecular pathogenesis of glomerular disease using human-based genotype and gene expression data. The applicant will work with a multidisciplinary research team made up of nephrologists, computational geneticists, genetic epidemiologists, bioinformaticians, and wet-bench researchers.
The primary duties of the applicant will be to apply and extend existing analysis procedures to novel genotype and gene expression data sets derived from patients with glomerular kidney disease. This position requires an individual capable of communicating with students and researchers, handling and prioritizing tasks across multiple projects, and working independently on critical tasks. The applicant must have excellent written and oral communication skills, strong analytical skills, excellent judgment, and the ability to work under deadlines with general guidance.
Responsibilities*
Analysis of next-generation sequencing data (whole genome sequencing, targeted DNA sequencing, and RNA-seq). Installation and execution of established analysis pipelines for the identification of genome variants including SNPs, indels, and structural variants. Analysis of SNP data. Development of scripts/programs for the processing of genomic data, including quality control, statistical analysis, and functional interpretation. Maintenance and management of sequence data and analysis results. Analysis of data and results, communication with external collaborators, and contributions to the preparation of manuscripts, grants, and presentations is required.
Desired Qualifications*
MA/MS in computer science, bioinformatics, biostatistics, or a related field and experience working as computational genomics researcher or BA/BS in biology, genetics, molecular biology, biochemistry, or a related field and 2 years experience working in computational genomics and demonstrated expertise in bioinformatics. A working knowledge of basic principles of genetics/genomics such as gene structure, gene transcription is required. Experience with high-throughput genomic data, such as microarray, RNA-seq, DNA sequencing data is preferred. Experience with Unix/Linux and working with large datasets in a cluster-computing environment using job schedulers such as SGE, PBS, LSF, MOSIX or SLURM is preferred. Experience with a language such as python, perl, shell scripting, or sed/awk is required, and the knowledge of lower-level language such as C/C++ or Java is preferred. Knowledge of standard software for genomic and genetic analysis such as BLAST, BWA, samtools, GATK, PLINK, Bowtie, Cufflink, or BLAT is preferred. Basic statistics/data analysis abilities and experience with R is desired.
A critical qualification is a strong desire to contribute to a cutting-edge research program that combines computational approaches with genomics data to gain insights into the basic biology of genomes, evolution, population variation, and the genetic basis of phenotypic variation.
Interested candidates should send a CV and names of referees to Dr. Matthew Sampson, Assistant Professor, Department of Pediatric Nephrology, at email: [email protected]
(Department of Pediatric Nephrology. In close collaboration with the Center for Statistical Genetics, Department of Computational Medicine and Bioinformatics, and Department of Adult Nephrology)
Job Summary
We are seeking a highly skilled analyst/programmer interested in working at the intersection of cutting-edge genomics and systems biology of kidney disease. The applicant will make original contributions to a diverse set of scientific projects that seek to understand the molecular pathogenesis of glomerular disease using human-based genotype and gene expression data. The applicant will work with a multidisciplinary research team made up of nephrologists, computational geneticists, genetic epidemiologists, bioinformaticians, and wet-bench researchers.
The primary duties of the applicant will be to apply and extend existing analysis procedures to novel genotype and gene expression data sets derived from patients with glomerular kidney disease. This position requires an individual capable of communicating with students and researchers, handling and prioritizing tasks across multiple projects, and working independently on critical tasks. The applicant must have excellent written and oral communication skills, strong analytical skills, excellent judgment, and the ability to work under deadlines with general guidance.
Responsibilities*
Analysis of next-generation sequencing data (whole genome sequencing, targeted DNA sequencing, and RNA-seq). Installation and execution of established analysis pipelines for the identification of genome variants including SNPs, indels, and structural variants. Analysis of SNP data. Development of scripts/programs for the processing of genomic data, including quality control, statistical analysis, and functional interpretation. Maintenance and management of sequence data and analysis results. Analysis of data and results, communication with external collaborators, and contributions to the preparation of manuscripts, grants, and presentations is required.
Desired Qualifications*
MA/MS in computer science, bioinformatics, biostatistics, or a related field and experience working as computational genomics researcher or BA/BS in biology, genetics, molecular biology, biochemistry, or a related field and 2 years experience working in computational genomics and demonstrated expertise in bioinformatics. A working knowledge of basic principles of genetics/genomics such as gene structure, gene transcription is required. Experience with high-throughput genomic data, such as microarray, RNA-seq, DNA sequencing data is preferred. Experience with Unix/Linux and working with large datasets in a cluster-computing environment using job schedulers such as SGE, PBS, LSF, MOSIX or SLURM is preferred. Experience with a language such as python, perl, shell scripting, or sed/awk is required, and the knowledge of lower-level language such as C/C++ or Java is preferred. Knowledge of standard software for genomic and genetic analysis such as BLAST, BWA, samtools, GATK, PLINK, Bowtie, Cufflink, or BLAT is preferred. Basic statistics/data analysis abilities and experience with R is desired.
A critical qualification is a strong desire to contribute to a cutting-edge research program that combines computational approaches with genomics data to gain insights into the basic biology of genomes, evolution, population variation, and the genetic basis of phenotypic variation.
Interested candidates should send a CV and names of referees to Dr. Matthew Sampson, Assistant Professor, Department of Pediatric Nephrology, at email: [email protected]