Bioinformatics Scientist

The position will independently provide support services to satisfy the overall operational objectives of the National Institute on Environmental Health Sciences.

• Ph.D. in Bioinformatics, Biostatistics, Computational Biology or a biological/life science

• Mathematics and Computer Science

• Biology

• Environmental Science

• Genetics

• Molecular Biology

• R

• Python

• MATLAB

• Linux

• PERL

• Unix

• Shell

• Java

• Next gen sequencing data analysis: Bulk RNA-Sequencing

• Next gen sequencing data analysis

• Clinical and/or translational research

• Single Cell RNA-Sequencing

• Work with large data sets

• Microarray data analysis

• Pipeline development

• Methylation Analysis

• Multi-omics Analysis

• Cluster Analysis

• Core facility

• Work products and documents related to conducting data analyses on NextGen sequencing data; analyzing and interpreting data from genomic platforms, including expression microarrays and others. - Ad-Hoc

• Work products and documents related to identifying and discovering analyses of differentially expressed genes; calculating fold change, p-values, multiple test adjustments and custom analyses; conducting data quality analyses/assessments, analyses of raw and normalized data using graphical techniques. - Ad-Hoc

• Work products and documents related to developing and/or managing workflows,
  experimental design, analyses of data quality, genome and meta-genomic context and
  others. - Ad-Hoc

• Work products and documents related to writing custom programs and algorithms; designing models summarizing/explaining experimental data; preparing reports and publication quality graphics; participating in meetings. - Ad-Hoc

• Conduct analyses on NextGen sequencing data including data derived in ChIP-Seq, RNA-Seq, miRNA-Seq and other experimental
  models. - 1
• Conduct analysis and interpretation on data from genomic platforms including expression, exon, tiling, promoter and others array types. - 2
• Conduct data analysis and interpretation on other large data types in genomic context. - 3
• Establish and maintain workflows including experimental design, analyses of data quality, genome and meta-genome integration and
  others. - 4
• Write utility scripts, macros and/or custom programs or algorithms in support of biological discovery. - 5
• Coordinate with biologists and/or other bioinformaticians in the design of models summarizing and explaining experimental data;
  provide interpretive analyses of data derived from different experimental platforms to generate biological meaning.

• Prepare reports and publication quality graphics summarizing experimental data including providing written documents

• Participate in meetings with biologists; present findings to individuals and groups.