Bioinformatics / Comparative Genomics R&D Staff Member

A highly motivated individual is sought to work with a diverse group of scientists focused on the bioinformatics aspects of ORNL's initiative in complex biological systems. ORNL engages in DOE mission driven research in programs in comparative and functional genomics, structural biology, and computational biology and bioinformatics. The individual will work on existing projects in bioenergy and microbial-plant interfaces and build a program levering ORNL's distinctive expertise and facilities in in a wide range of biological fields that focus on the functioning of complex biological systems. The successful candidate will work in a highly skilled, team-oriented environment applying knowledge of cellular, molecular, and computational biology to create novel methods and testable scientific hypotheses.   Oak Ridge National Laboratory (ORNL) is one of the world’s premier centers for R&D on energy production, distribution, and use and on the effects of energy technologies and decisions on society. Clean, efficient, safe production and use of energy have long been our goals in research and development. At ORNL, unique facilities for energy-related R&D are used both for technology development and for fundamental investigations in the basic energy sciences that underpin the technology work. Major Duties/Responsibilities   The successful applicant will be leading cross-functional research efforts in a team of high-level scientific and technical personnel to accomplish project goals and timelines from initial concept through successful completion. This position will utilize principles and methods of systems biology and will be responsible for the development of a professionally recognized independent research program in integrated bioinformatics. The candidate is expected to maintain a competitive and innovative research program. Duties include: -Responsibility for conceptualizing, designing, developing, and integrating complex databases, data analysis, data mining, and computational modeling. -Developing and integrating data sets from multiple platforms which could include phenotypic and experimental data combined with “OMICS” platforms such as; genomics, proteomics and metabolomics -Partnering with peers to identify opportunities for process improvement, knowledge transfer, and reuse of existing informatics solutions, algorithms, platforms and pipelines for data analysis and integration. -Being a primary consultant for staff regarding informatics requirements, data analysis, analysis platforms, data correlative development, and representation -Mentoring others in the techniques of data collection, mining and management - Applying knowledge of bioinformatics algorithms and analysis platforms to consult on and lead computational biology projects - Understanding and instructing on the strengths and limitations of analysis platforms as they apply to experimental endpoints and will readily be able to set expectations and defend results through direct communication with principal investigators and their staff - Developing a strong extramural research program resulting in high profile publications and independent funding