To develop novel tools for bioinformatic analysis of metabolomic data generated by mass spectrometry and to analyze and manage the data in useful biomarker profiles for drug screening, diagnostic tools and potential therapeutic targets. The candidate should have a track record demonstrating the ability to be self-motivated and self-directing, to develop realistic project plans with timelines, and to solve problems using application of scientific theory.
Essential Job Duties and Responsibilities
Assist in the experimental design of projects.
Design and implement statistical analysis of metabolomic data.
Carryout both multivariate and univariate statistics applicable to biomarker discovery and validation.
Evaluate and development internal data analysis tools to increase the throughput of discovery based experiments.
Maintain and analyze very large and dynamic datasets.
Work closely with biologists and analytical chemists.
Write grant applications at the direction of the Chief Scientific Officer in collaboration with other scientific staff.
Keep and maintain accurate and detailed records of data analysis procedures and results.
Contribute to the development of novel algorithms and data visualization tools.
Education and Experience
Masters degree in Biostatistics or related discipline with a background in “omics” type data analysis methods.
A strong knowledge of statistical programming in R and experience in Matlab or Mathematica. The ability to use Perl and other scripting languages are desired, but not required.
At least two years experience in bioinformatics research and development, preferably in metabolomic or proteomic data analysis.
An understanding of mass spectrometry based data analysis and manipulation is desired, but not required.
