This position will interact remotely with the main Bioinformatics group situated in Montreal, Canada with several visits to Montreal per year and stay in close communication. As the sole Bioinformatician in Menlo Park, the individual will be spearheading study design, data analysis, results visualization and reporting, primarily for Menlo Park projects. Thus he/she will work independently but closely with proteomics scientists in a results-driven, collaborative environment. He/she will be responsible for the choice of statistical methodology, the writing of the statistical analysis plan, carrying out the analyses, integration of peptide profiling and peptide identification data and providing interpretations and conclusions from the results in a report for each project in a timely fashion.

The successful candidate will also perform ad-hoc analyses and advise the scientific team on general bioinformatics and statistics questions, platform design, study design, and data analysis.

The Bioinformatician is expected to propose and implement new quality control and data analysis procedures and/or improve existing ones.

Responsibilities:

• Write formal Statistical Analysis Plans for complex studies.
• Perform statistical analyses of data (normalization, differential expression, classification) and interpret results to ensure validity of conclusions.
• Provide clear visualization and summary of statistical analysis results.
• Write and review statistical sections for protocols and study reports.
• Propose and implement novel quality control and data analysis procedures.
• Provide significant input into the design of clinical proteomic studies.
• Create randomization schemes for sample processing.
• Integrate profiling data with MS/MS identification data.
• Provide scientific recommendations on how to improve the quality of the results and the research platform.
• Perform ad-hoc analysis to evaluate data quality or improve the understanding of the results.

Skills Requirements:

• MS or Ph.D. in Bioinformatics, Biostatistics or related field of study.
• Five years of work experience in genomics, proteomics or related field.
• Experience with a variety of statistical methods including general linear models (e.g., ANOVA), logistic regression, univariate and multivariate analyses, and longitudinal analyses.
• Experience in predictive modeling, classification and discriminant analysis is strongly desirable.
• Experience with integrating LC-MS and MS/MS data, determining MS/MS quality, rolling up bottoms-up proteomics data to the protein level is a plus.
• Experience with R (preferred) or Matlab.
• Experience with Perl and/or C++.
• Solid understanding of molecular biology, proteomics and mass spectrometry.
• Strong oral and written communication skills.
• Excellent interpersonal skills and ability to work collaboratively as part of a fast paced research team.

Interested candidates should submit their résumé to: