BACKGROUND

RESPONSIBILITIES

• Foster, coordinate, and guide where needed the development of bioinformatics software for the direct support of gene and genome engineering.
• Proactively identify and coordinate the creation/procurement, integration, and deployment of software tools for the management of large, complex data sets.
• Work closely with project managers & scientists, members of the computational biology group, and other competency groups to identify, develop and maintain informatics tools & workflows.
• Provide mentorship and guidance to group members.
• Provide analytical, statistical, organizational, and strategic guidance and expertise as required.
• Develop budgets and manage the procurement and implementation of software systems and services.
• Manage technical staff.
• Seek and evaluate new, cutting-edge technologies in computational biology and metabolic & cellular engineering.
• Work with senior management and all levels of the scientific staff to effect strategic innovation in central and related fields.

REQUIREMENTS/REQUIREMENTS

• PhD in Bioinformatics, Statistics, Computer Science, Engineering or related discipline and 10+ years of relevant experience in biotechnology, systems biology, software engineering, and/or statistical analysis
• Knowledge of one or more programming languages such as Java, Perl, Python, C++ and one or more relational database management systems
• Knowledge of classical and modern statistical techniques (Bayesian) and familiarity with statistical computing tools such as R and MATLAB
• Knowledge of modern software engineering development best practices and object oriented design
• Deep knowledge of bioinformatics tool development and biological data and systems analysis
• Excellent ability to communicate with molecular biologists, analytical biochemists, and metabolic/cellular engineers and a broad understanding of the science behind these disciplines
• Ability to use advanced software tools in an innovative fashion to address systems, data analysis, and data presentation problems
• Knowledge and experience of methods for storing, analyzing, and presenting/visualizing large data sets, especially those related to genomics, transcriptomics, proteomics, and metabolomics
• Ability to work independently and with other members of the scientific and engineering staff to gather requirements and implement software systems
• Ability to develop and implement algorithms for data analysis
• Ability to operate in heterogeneous hardware and software environments
• Ability to communicate foreign and/or complicated concepts to non-experts and management as well as influence colleagues and decision makers to adopt novel approaches to data generation and analysis
• High degree of intellectual curiosity and desire to immerse oneself in new and cutting edge science & technology
• Excellent oral and written communication, presentation and interpersonal skills

HOW TO APPLY

POLICY