Computational Biologist - Postdoctoral Researcher | Livermore, California, United States | Lawrence Livermore National Laboratory

Position:	Computational Biologist - Postdoctoral Researcher
Institution:	Lawrence Livermore National Laboratory
Location:	Livermore, California, United States
Duties:	Collaborate with researchers in protein engineering, structural modeling, bioinformatics, software engineering, and High Performance Computing; Develop bioinformatics tools and software that enable experimental data integration, protein sequence design, and high-density encoding of synthetic functions in microorganisms; Inform the acquisition of and leverage large experimental datasets to enable AI-enabled protein design and functional assessment; Carry out development of moderately complex data analysis algorithms to address bioinformatics needs; Design technical solutions with limited direction, participating as a member of a multidisciplinary team to design/implement software and perform data analysis
Requirements:	Ph.D. in Bioinformatics, Computational Biology, Computer Science, Engineering, or another technical discipline providing an underlying skillset in data analysis, bioinformatics, and machine learning techniques; Comprehensive knowledge of one or more of the following: scientific data analysis, statistical analysis, data management technologies, protein structure analysis, protein structure modeling, homology modeling, and protein engineering; Experience developing and/or applying new bioinformatics software tools and workflow/pipelines to solve problems in computational protein analysis

Text:	Computational Biologist - Postdoctoral Researcher Collaborate with researchers in protein engineering, structural modeling, bioinformatics, software engineering, and High Performance Computing; Develop bioinformatics tools and software that enable experimental data integration, protein sequence design, and high-density encoding of synthetic functions in microorganisms; Inform the acquisition of and leverage large experimental datasets to enable AI-enabled protein design and functional assessment; Carry out development of moderately complex data analysis algorithms to address bioinformatics needs; Design technical solutions with limited direction, participating as a member of a multidisciplinary team to design/implement software and perform data analysis Ph.D. in Bioinformatics, Computational Biology, Computer Science, Engineering, or another technical discipline providing an underlying skillset in data analysis, bioinformatics, and machine learning techniques; Comprehensive knowledge of one or more of the following: scientific data analysis, statistical analysis, data management technologies, protein structure analysis, protein structure modeling, homology modeling, and protein engineering; Experience developing and/or applying new bioinformatics software tools and workflow/pipelines to solve problems in computational protein analysis