Job ID:
Job date: 2018-02-04
End Date:
Company : University of Michigan Country : Role : Research Scientist
Job date: 2018-02-04
End Date:
Company : University of Michigan Country : Role : Research Scientist
Job Description:
We are seeking a highly skilled and enthusiastic computational analyst/bioinformatician to work at the intersection of cutting-edge genomics, transcriptomics and systems biology of kidney disease with a highly motivated and energetic team. 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 nextgeneration DNA and RNA sequencing data and clinical information. 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 utilize our core genetic and gene expression data sets derived from patients with glomerular kidney disease to (1) identify statistically associated genomic variants, (2) use genetic epidemiology approaches to identify associations between these variants and clinical characteristics and outcomes (3) functionally characterize these set of variants using computational and bioinformatics tools and methods. 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) using statistical packages, such as R, to identify statistically significant associations. Ability to integrate our data with other large-scale existing datasets (e.g. ENCODE, 1000 Genomes) to visualize our variants in the context of existing data. Use of bioinformatics software programs to functionally annotate our variants of interest (e.g. pathway, network, motif, promoter analyses of statistically associated variants). Ability to perform potentially complex queries of our large-scale datasets to answer specific questions about genetic variant relationships with clinical outcomes. Generation of power calculations and preliminary data for grants. Communication of results with internal and external collaborators, and contributions to the preparation of manuscripts, grants, and presentations is required. Required Qualifications:
Additional Info:
Background Screening Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Application Deadline Job openings are posted for a minimum of seven calendar days. This job may be removed from posting boards and filled anytime after the minimum posting period has ended.[Click Here to Access the Original Job Post]
We are seeking a highly skilled and enthusiastic computational analyst/bioinformatician to work at the intersection of cutting-edge genomics, transcriptomics and systems biology of kidney disease with a highly motivated and energetic team. 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 nextgeneration DNA and RNA sequencing data and clinical information. 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 utilize our core genetic and gene expression data sets derived from patients with glomerular kidney disease to (1) identify statistically associated genomic variants, (2) use genetic epidemiology approaches to identify associations between these variants and clinical characteristics and outcomes (3) functionally characterize these set of variants using computational and bioinformatics tools and methods. 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) using statistical packages, such as R, to identify statistically significant associations. Ability to integrate our data with other large-scale existing datasets (e.g. ENCODE, 1000 Genomes) to visualize our variants in the context of existing data. Use of bioinformatics software programs to functionally annotate our variants of interest (e.g. pathway, network, motif, promoter analyses of statistically associated variants). Ability to perform potentially complex queries of our large-scale datasets to answer specific questions about genetic variant relationships with clinical outcomes. Generation of power calculations and preliminary data for grants. Communication of results with internal and external collaborators, and contributions to the preparation of manuscripts, grants, and presentations is required. Required Qualifications:
- Bachelor’s Degree is required. 1-3 years of experience in computer science, bioinformatics, biostatistics, or a related field.
- Experience working in biology, genetics, molecular biology, biochemistry, or a related field.
- Basic statistics/data analysis abilities and experience with a statistical package such as R is required.
- A working knowledge of basic principles of genetics/genomics such as gene structure, gene transcription, and epigenetics is required
- Master’s Degree preferred.
- Experience with high-throughput genomic data, such as microarray, RNA-seq, DNA sequencing data is preferred.
- Experience with a language such as python, perl, shell scripting is preferred.
- Knowledge of standard software for genomic and genetic analysis such as BLAST, BWA, samtools, GATK, PLINK, Bowtie, Cufflink, or BLAT is preferred.
- A critical qualification is a strong desire to contribute to a research program that applies computational approaches to answer the question of how genetic variation contributes to the pathogenesis and progression of kidney disease in children and adults. More information at sampsonlab.org.
Requeriments :
Skills :
- Biochemistry
- Biology
- DNA sequencing
- Genetics
- genomic
- Microarray
- molecular biology
- Next Generation Sequencing
- Programing in Python
- Programming in PERL
- Programming in R
- RNA-seq
- Shell scripting
- Statistics
Areas :
Additional Info:
Background Screening Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Application Deadline Job openings are posted for a minimum of seven calendar days. This job may be removed from posting boards and filled anytime after the minimum posting period has ended.[Click Here to Access the Original Job Post]