RESPONSIBILITIES

• Responsible for complex analysis on biomedical data produced from a variety of biotechnology platforms including microarrays, next-generation sequencing systems, and scientific imaging.
• Designs, develops, improves, modifies, and operates data analysis pipelines.
• Develops bioinformatics pipelines or uses advanced software packages (e.g. extant) in conducting data analysis for biomedical datasets.
• Works closely with experimental researchers to understand analytical needs, provide technical consultation, design analytical approaches, generate/provide analysis results and reports, project reports and perform requested custom analyses.
• Independently performs post-processing statistical analysis of results and interprets results.
• Contributes to the evaluation and recommendation of new software tools to meet the growing needs of the research community at St Jude Children's Research Hospital (SJCRH).
• Designs and prepares materials for training lab scientists on software usage and data analysis techniques.
• Manages projects and coordinates other efforts related to analysis and infrastructure as directed.

REQUIREMENTS

• Bachelor's degree is required.
• Six (6) years of relevant experience is required.

PREFERENCES

• Master's degree or PHD is preferred.
• Four (4) years of relevant experience may be acceptable with a Master's degree.
• No experience may be acceptable with a PhD in Computer Science or Bioinformatics, with a background in the biological sciences.
• Experience in programming (Python, Java, C/C++, Perl, or other programming/scripting languages) under Linux/Unix environment is preferred.
• Experience with and the ability to deal with a wide range of users is preferred.
• Experience in independent data analyses and project management is preferred.
• End-user support and training experience is preferred.
• Experience with open-source software development preferred.
• Experience in the development of algorithms, statistical methods, or scientific software is preferred.
• Experience in next-generation sequence analysis or imaging analysis is preferred.
• Experience in working with high-throughput data sets in a highly competitive environment is preferred.
• Experience in working in a team project is preferred.
• Cross-training in biological sciences (e.g. genomics, genetics, transcriptomics, and epigenetics) preferred
• Scripting experience using a statistics package such as R, S-Plus or SAS preferred.
• Experience in personnel management is preferred.

LOCALE

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