11 statistics Fellowship positions at Lawrence Berkeley National Laboratory in United-states
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and contribute to research proposals. Publish developed algorithms as software packages. What is Required: Ph.D. in the last 3 years in Machine Learning, Applied Mathematics, Statistics, Computational
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team environment, including backgrounds in biology, chemistry, earth sciences, statistics, physics, energy technologies, materials science, engineering, and computer science. Analyze and summarize data
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, PacBio, and Oxford Nanopore technologies. Experience with standard bioinformatics, statistical methods, and tools (i.e., sequencing databases, assemblers, aligners, and programming languages such as Python
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, and techno economic analysis. Work in a multidisciplinary team environment, including backgrounds in biology, chemistry, earth sciences, statistics, physics, energy technologies, materials science, and
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diagnostics methods. Knowledge of solid-polymer electrolytes, composite membranes, mechanics, and polymer chemistry. Familiarity with data curation and visualization, statistics, and advanced data analysis
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prototype detector systems. Design, set up, and execute experiments to characterize and evaluate detector performance. Analyze experimental data using advanced statistical and data analysis techniques, and
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performance. Analyze experimental data using advanced statistical and data analysis techniques, and develop custom data analysis tools and algorithms as necessary. Prepare high-quality manuscripts
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, Biogeochemistry, Molecular Biology and an understanding of key and complex biological concepts including genes, pathways, and microbial phylogeny. Experience with UNIX utilities and filesystems, R statistical
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concepts including genes, pathways, and microbial phylogeny. Experience with UNIX utilities and filesystems, R statistical analysis platform, and standard bioinformatics tools and databases. Excellent oral
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interdisciplinary research team. Desired Qualifications: Experience with standard bioinformatics and statistical methods and tools (examples include sequencing databases, assemblers, and aligners, programming