Computational Biology Postdoctoral Scholar

Updated: over 2 years ago
Location: Berkeley, CALIFORNIA
Deadline: The position may have been removed or expired!

Lawrence Berkeley Lab’s (LBL ) Joint Genome Institute (JGI ) Division has an opening for a ​​Computational Biology Postdoctoral Scholar to join the Algal and Fungal Program. 

 

As a Genome Science User Facility, the JGI provides the global research community with access to advanced genome science capabilities in support of the US Department of Energy’s missions in bioenergy, carbon cycling and biogeochemistry. Our team leads the high-throughput sequencing and analysis of reference algal genomes and the generation of multi-omics datasets for functional genomics and metabolic modeling. This position will focus on the analysis and integration of multi-omics datasets of Chlamydomonas mutant strains with the goal of predicting functions of novel genes involved in photosynthesis.


 

What You Will Do:

  • Analyze and integrate genomics, transcriptomics, metabolomics and other biological datasets of microalgae.
  • Apply machine learning, network modeling and other computational approaches to large multidimensional datasets.
  • Annotate and analyze algal genomes.
  • Perform comparative genomic analysis.
  • Write scientific research papers and reports and publish in peer reviewed journals
  • Attend and present at scientific meetings and workshops.

 What is Required:

  • Recent PhD in Bioinformatics, Biology, Microbiology, Life Sciences or a related field with an interest in functional genomics.
  • Expertise in any of the following: analyses of large-scale biological sequence data sets, transcriptomics, and metabolomics.
  •  Experience in annotation and/or analysis of eukaryotic genomes.
  •  Experience with standard bioinformatics methods and tools for sequence analysis.
  •  Proficiency with scientific programming languages. (e.g., Python and/or R)
  •  Excellent oral and written communication skills.
  • Strong organizational and record-keeping skills.
  • Ability to work independently as well as part of a diverse team.

 Desired Qualifications:

  • Knowledge of algal biology and genomics.
  • Experience applying machine learning and data integration methods to scientific problems.
  • Experience with SQL or relational databases.
  • Experience working in collaborative teams.

Notes:

  • This is a full-time 1 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.
  • Diversity, equity, and inclusion are core values at Berkeley Lab. Our excellence can only be fully realized by faculty, students, and staff who share our commitment to these values. Successful candidates for our faculty positions will demonstrate evidence of a commitment to advancing equity and inclusion.
  • Work will be primarily performed at:Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

 

Learn About Us:

JGI & Berkeley Lab: A View to Fuel Innovative Science in the Public Interest

They say it’s all about location and Berkeley Lab has it all: a view above the San Francisco Bay, cool breezes, and world-class multidisciplinary science within a diverse and respectful research ecosystem of 5,000 people. Nearly 90 years ago, Ernest Orlando Lawrence, the inventor of the cyclotron, brought physicists, biologists, engineers and mathematicians together in Berkeley above the University of California campus to tackle the most urgent scientific challenges. Today, after garnering 13 Nobel Prizes, Berkeley Lab has sustained and grown that tradition of open, interdisciplinary team science, exemplified by how the U.S. Department of Energy Joint Genome Institute (JGI) addresses the most pressing energy and environmental challenges using integrative genome science approaches. JGI takes up residence in the new, state-of-the-art Integrative Genomics Building (IGB) along with the U.S. Department of Energy Systems Biology Knowledgebase (KBase) to expand the frontiers of energy and environmental science in partnership with the worldwide community of researchers. Will you join us and be a critical part of our next ground-breaking discoveries?

 

Berkeley Lab (LBNL) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.

 

Working at Berkeley Lab has many rewards including a competitive compensation program, excellent health and welfare programs, a retirement program that is second to none, and outstanding development opportunities.  To view information about the many rewards that are offered at Berkeley Lab- Click Here .

 

Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."

 

Lawrence Berkeley National Laboratory encourages applications from women, minorities, veterans, and other underrepresented groups presently considering scientific research careers.



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