<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:x="urn:schemas-microsoft-com:office:excel" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"><head><meta http-equiv=Content-Type content="text/html; charset=us-ascii"><meta name=Generator content="Microsoft Word 15 (filtered medium)"><style><!--
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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal><span style='font-size:11.0pt'>1) Earth Scientist, Cloud-Aerosol Interactions via Data Analysis & Modeling<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'>Pacific Northwest National Laboratory (PNNL) is recruiting an innovative early career scientist interested in inter-disciplinary research associated with developing new scientific insights into the lifecycle of organic aerosols and their impact on cloud properties using data analysis and modeling tools. This involves having a deep understanding of microphysical processes of liquid, ice, and mixed-phase clouds and how those processes are perturbed by aerosols. The candidate is also expected to be familiar with organic gas- and particle-phase chemistry associated with the formation, growth, and aging of secondary organic aerosol (SOA) since and their effect on cloud condensation and ice nuclei (CCN & IN). You will be expected to have an understanding of how aerosol properties affect cloud formation and lifetimes, absorption and scattering of light, and how meteorological processes influence the aerosol lifecycle. A strong grasp of aerosol mixing state, transport over multiple scales, and fate via wet removal and dry deposition of particles is desirable. Hypotheses regarding new process-level understanding of cloud-aerosol interactions will be evaluated within a multi-scale modeling context and rigorously evaluated using a wide range meteorological, chemical, and aerosol field campaign measurements. Knowledge of measurement uncertainty and its effect on the interpretation of model predictions is important.<br><br>You will be expected to work as part of a team of scientists at PNNL with experience in both measuring and modeling aerosols. Ultimately, you will be expected to develop your own hypotheses and execute a research plan that addresses those hypotheses.<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'><a href="https://pnnl.jibeapply.com/jobs/308191?lang=en-us">https://pnnl.jibeapply.com/jobs/308191?lang=en-us</a><o:p></o:p></span></p><p class=MsoNormal><b><span style='font-size:11.0pt'><o:p> </o:p></span></b></p><p class=MsoNormal><span style='font-size:11.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'>2) Atmospheric Data Analyst<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'>Pacific Northwest National Laboratory (PNNL) is recruiting an early career scientist interested in developing new scientific insights into the initiation, organization, dynamics, and microphysics of convective cloud populations. You will be expected to work as part of a team of scientists investigating convective clouds, with a long-term goal of using new observational, theoretical and modeling insights to improve representation of convection and microphysical processes in both high resolution regional and global models. Specifically, you will be expected to apply modern statistical and computational methods to analyze large data-sets from observations (e.g. radar, satellite) and models (LES, regional-scale, global climate) to understand cloud-environment interactions that lead to convective transitions. Two-way interactions of microphysical processes with convective circulations such as updrafts, downdrafts, and cold pools on fine spatiotemporal scales are of particular interest. The ability of multi-scale models and variable complexity physics parameterizations to capture observed cloud and environmental processes will be critical in predicting the convective life cycle. You will identify sources of model biases through innovative model sensitivity experiments design and evaluation. <br><br>An ability to analyze large observational (e.g. radar, satellite) and model (LES, regional-scale, global climate) datasets and to pose hypotheses that tease out new insights from the large datasets is critical. Using data assimilation techniques to constrain environmental conditions in models and better represent cloud distributions is desirable. In collaboration with others on the team, you may also contribute to analyzing the ability of models to reproduce the observed impacts of convective clouds and precipitation on surface properties, aerosol redistribution, and boundary layer evolution with feedbacks to subsequent convective cloud development.<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt'><a href="https://pnnl.jibeapply.com/jobs/308075?lang=en-us">https://pnnl.jibeapply.com/jobs/308075?lang=en-us</a><b><o:p></o:p></b></span></p><p class=MsoNormal><span style='font-size:11.0pt'><o:p> </o:p></span></p></div></body></html>