Lawrence Berkeley National Lab's (LBNL) Environmental Genomics & Systems Biology Division has an opening for a Computational Biology Postdoctoral Fellow to join the Department of Energy (DOE) Systems Biology Knowledgebase (KBase) team. The successful candidate will be supervised by Principal Investigator, Adam Arkin and Scientist, Paramvir Dehal.
In this exciting role, you will work with the KBase and Research team leads in collaboration with targeted users to develop advanced functionality and analysis in KBase. In this role, you will develop and execute novel machine learning methods for predictive biology for microbes, plants, and their communities. You will collaborate with computational scientists and biologists to develop new GPU-enabled infrastructure on the National Energy Research Scientific Computing Center (NERSC)'s new Cray supercomputer, "Perlmutter", and you have the opportunity to pursue and lead towards publication of novel genomics-based research that leverages the KBase Knowledge Engine and Relation Engine.
The Department of Energy Systems Biology Knowledgebase (KBase) is a computational platform designed to meet the key challenges of systems biology: predicting and designing biological function. KBase integrates numerous biological datasets and analysis tools in a unified, extensible system that allows researchers to collaboratively generate and test hypotheses about biological functions and interactions. The project's long-term goal is to help researchers understand how plants and microbes interact with and affect each other and environmental processes and how these interactions could be harnessed for sustainable bioenergy and environmental solutions. KBase is a multi-institutional collaboration involving about 30 researchers at four national laboratories (LBNL, Argonne, Brookhaven, and Oak Ridge) and several universities.
Work will be performed at Lawrence Berkeley National Laboratory, a national lab that offers a research environment similar to academic institutions with a reasonable work/life balance. You will work with a diverse and talented team of biologists, computer scientists, and developers, and will have many opportunities to broaden their knowledge and meaningfully expand their collaborative network. Travel to other KBase sites for two-day planning meetings will occur several times a year.What You Will Do:
What is Required:
- With KBase leadership, collaborate with targeted KBase users and other stakeholders to identify high value science that can be performed with suitable extensions to the KBase platform and data sets.
- Develop, package, and apply new and community computational methods in the KBase platform, which will be shared and disseminated across the microbiome community.
- Work with the KBase team to develop the integrated data science platform to support inference across system reference source and shared user data.
- Work with targeted users to perform sophisticated analyses of heterogeneous biological data of plants, microbes and their communities to discover and predict biological function and behavior and compare against experimental observations.
- Publish scientific papers in peer-reviewed journals and present findings at seminars and conferences.
- Collaborate with other members of the project research team, both internal and external to Berkeley Lab and develop new collaborations as appropriate to further the scientific goals of the program.
- Ph.D. within the last three years in computer science, data science, machine learning, chemical engineering, bioengineering, chemistry, biochemistry, chemical biology, plant biology, microbiology, bioinformatics, computational biology, or related field.
- Strong background in programming, data science and/or computational biology.
- Proven ability to perform independent research and organize data for publication and presentations.
- Demonstrated ability to interact effectively with technical and scientific staff.
- Ability to work independently and in a team environment.
- Demonstrated ingenuity in dealing with complex problems.
- Demonstrated strength and efficiency in technical writing.
- Strong track record in developing software tools.
- Strong experience with software engineering best practices.
- Experience/familiarity with AGILE project management.
- This is a full-time 2 year postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
- This position is represented by a union for collective bargaining purposes.
- Salary will be predetermined based on postdoctoral step rates.
- This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
- Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
- Flexible work options are available.
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