20 Statistics positions at Lawrence Berkeley National Laboratory in california in United States
-
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
-
out statistical analysis and prepare results for publication. Document and communicate research results through publications, such as technical reports and journal manuscripts. Review published
-
interdisciplinary research team. Desired Qualifications: Experience with standard bioinformatics and statistical methods and tools (examples include sequencing databases, assemblers, and aligners, programming
-
/frameworks (e.g., TensorFlow, PyTorch). Proficiency in field-programmable gate array (FPGA) programming in RTL design and verification. Strong background in ML, statistics, and mathematics, with practical
-
in basic statistics. Desired start date is May 1, 2024 but earlier or later start dates will be considered. Apply by March 20, 2024 with the following application materials (the position will remain
-
of statistical methods suitable for durability and lifetime predictions. Design and execution of operando measurements aimed at determining degradation rates and mechanisms in PEC water splitting devices
-
the use of optimization tools, computing statistical analysis, and visualization software (e.g. python, R). Demonstrated ability to write high-quality technical publications. Excellent oral and written
-
quality. Proficiency with MS Office and strong skills in at least one programming language (C/C++, Python, R). Familiarity with geospatial information systems (GIS). Familiarity with statistical analysis
-
; electrification; etc. Knowledge of residential and commercial building energy policy and codes. Knowledge in statistics related to quantifying model prediction errors, sensitivity/uncertainty analysis, regression
-
to the topic at hand, including primary data, economic, and statistical analyses; modeling; and survey and interview-based research. We are conducting cost-effectiveness analysis and modeling to understand