Computational Systems Biologist at Oak Ridge National Laboratory in Oak Ridge, Tennessee

Job Description:

Requisition Id4407

PURPOSE
The Computational and Predictive Biology Group (CPB) in the Biosciences Division at the Oak Ridge National Laboratory (ORNL) seeks applicants for a full-time staff scientist position. The Biosciences Division at ORNL is focused on advancing science and technology to better understand complex biological systems and their relationship with the environment. The Division has expertise and special facilities in genomics, computational biology, microbiology, microbial ecology, biophysics and structural biology, and plant sciences. The CPB group is interdisciplinary focusing on technology development with specific interests in systems biology, network analysis and information flow, and collaborating with scientists from related experimental, computational, and technical disciplines, to build increasingly detailed computational models of biological systems. These efforts improve accuracy and statistical power, and thereby enable researchers to gain new insights and predict properties and outcomes of biological systems that advance scientific understanding.

Members of our group work on a range of problems, including investigation of bioenergy plants as feedstock for advanced biofuels; how microbes interact with plants under natural and engineered conditions; and how an individual's genes may lead them to be more susceptible to pain and opioid addiction. To tackle such problems we also develop new technical methods and systems such as KBase (the Department of Energy Systems Biology Knowledgebase), and work with researchers at the Oak Ridge Leadership Computing Facility to develop exascale applications that run on some of the world's fastest supercomputers.

We are seeking a Staff Scientist to develop and apply computational methods to explore biological processes at all levels of life systems organization from atomic to ecological. Research experiments include large scale laboratory and field experimental data acquisition, management, organization and analysis to derive insight and hypotheses suitable for further experimental validation, and improve researchers' ability to further advance understanding of biological systems for projects at ORNL including the Center for Bioenergy Innovation, Plant Microbes Interfaces, and Human Systems Biology/Clinical Genomics efforts that also include access to suitable large-scale computational resources.

In this position, you will be taking a lead role in the development and Integration of genomics with other omics data (transcriptomics, metabolomics, proteomics, microbiomics, etc.) plus environmental information for improving prediction and functional inference, and in developing pipelines to process and analyze high throughput phenotyping data for input into systems biology contexts. Further questions about this position should be directed to Bob Cottingham ()

MAJOR DUTIES / RESPONSIBILITIES
- Development and support of data modeling, integration and management, along with associated computational and machine/deep learning environments and interfaces for systems biology research.
- Analyze large biological data sets to build accurate predictive models of biological processes and publish original work.
- Collaborate with internal and external researchers to analyze and interpret novel results using newly derived methods.
- Contribute to ongoing projects in the group and successfully define and develop their own projects.
- Manage projects to drive them to timely delivery and publication, while mentoring students and postdocs
- Design and implement applications and data models to advance plant science research in the KBase cyberinfrastructure

QUALIFICATIONS REQUIRED
- A doctoral degree in a computer science, computational biology, bioinformatics, systems biology, biology, genetics or related field
- Minimum of three years postdoctoral experience in computational biology
- Strong computational and machine/deep learning expertise, and a solid background in programming, statistics, and computational techniques
- Familiar with large-scale data analysis and understanding of data models to represent biological concepts
- Strong understanding of genomic-assisted breeding approaches, including experience implementing high throughput GWAS and Genomic Selection
- Strong experience with KBase including building Narratives, data upload, code cells, and SDK App development and deployment
- Experience developing custom scripts and pipelines for multi-omic data analysis, particularly using languages such as R, Python, Bash
- Comfortable with parallelizing analyses on HPC systems (e.g. slurm, PBS)
- Excellent written and oral communication skills and the ability to communicate in English to a scientific audience
- Familiarity with omics techniques and datasets such as RNASeq, proteomics, metabolic profiling, genomic variants, and genome resequencing and annotation
- Strong project management and organizational skills
- Experience with forest tree genetics (e.g. Poplar and Eucalyptus) a bonus

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.
We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer..