|From||Roger Brugge <email@example.com>|
|Date||Tue, 17 Sep 2019 21:18:39 +0000|
Multiple Postdoc / Project Scientist positions in Mike Pritchard’s group at the University of California, Irvine
Mike Pritchard, Associate Professor
Dept. of Earth System Sciences
University of California, Irvine, CA
I would like to hire three new senior members in my group at the University of California, Irvine. My main research interest is in advancing climate science by exploiting emerging atmospheric modeling algorithms of opportunity, including (1) turbulence- or cyclone-permitting variants of global cloud superparameterization that are just now becoming possible on next-gen (e.g. GPU-based) supercomputers, and (2) machine learning emulation of atmospheric physics for interpreting and accelerating the simulation of global climate system dynamics including the complexity of cloud physics. Funding for these new positions falls across 3 separate projects:
1. Achieving the potential of ultraparameterization to confront issues of boundary layer turbulence in cloud feedbacks to climate change [Funding: NSF, collaborative with Chris Bretherton & Peter Blossey @ U. Washington]. Over the past five years a UCI/UW/Stoney Brook collaboration has paved the way for high-resolution (i.e., boundary layer eddy-permitting) global superparameterization (Parishani et al. 2017,18), but the scientific ramifications of this have only begun to be explored. I welcome a new senior (postdoc- or research-scientist level) group member interested in understanding what relaxing traditional assumptions about the role of boundary layer turbulence means for broader climate dynamics, including the transitions and teleconnections between forms of low cloud organization and especially the aerosol-cloud indirect effect. Having expertise in global atmospheric dynamics, or the modeling or observation of aerosol-cloud interaction could be helpful; likewise interest in testing prototype algorithms on next generation supercomputers.
2. Exploring tropical cyclone or diurnal cycle dynamics at an ambitious new limit of global superparameterization (or machine learning emulation of same) [Funding: DOE, collaborative with a large team at LLNL, PNNL]. Funding for this position is through my role as one of two University Partners in the DOE’s Exascale Computing Project (ECP). It is an exciting time since the DOE-ECP has just succeeded in a 3-year mission to port the embedded cloud-resolving model (CRM) calculations used in superparameterization to graphical processor units, which are fueling a new step change in national supercomputing capacity. The reward is a newfound ability to run on the world’s best supercomputer (Summit, 200-petaflops), where previously unimaginable limits of cloud-resolving model resolution can now be explored. At UC Irvine I am looking for a scientist interested in engaging with this team of DOE researchers by helping analyze their first prototype model (i.e., the first 25-km exterior resolution superparameterized global model, with one million embedded CRMs), including its unfamiliar emergent diurnal cycle and hurricane dynamics. Applicants interested in machine learning for advancing climate prediction and dynamics are equally welcome: This model is generating a very data- and physics-rich library that could be helpful for training deep learning emulators to interpret geographic variations in convective system dynamics, or develop new data-driven convective parameterizations. The overall goal is to do such phenomenological and climate-change
science, while also helping with the DOE team’s broader vision of making this prototype into an operationally-useful convection-permitting model.
3. Machine learning emulation of aerosol nucleation physics [Funding: DOE, collaborative with PNNL]. Beyond ECP, the DOE also has an ambitious plan to make a global cloud resolving model that runs effectively on GPUs, with a great and growing team including leadership from Peter Caldwell at LLNL. I am seeking someone interested in helping with this effort by exploring whether machine learning emulation of aerosol-cloud interaction calculations is a viable strategy for porting costly calculations to GPU, and as a dynamical systems summary tool of the associated physics. Candidates with existing domain expertise on aerosol nucleation physics or aerosol cloud interaction are especially encouraged. Our group has had some recent success in emulating non-aerosol aspect of climate model physics (e.g. Rasp et al. 2018; Beucler et al., 2019) so in-house training on the practicalities of a deep learning workflow is available within the group already.
For all of these positions I am flexible about logistics and job titles -- I am mostly hunting for talent and meaningful collaboration with fun, independent people. For candidates interested in more than one of the above topics, creative project fusions spanning more than one theme could work. Start dates are flexible, as is to some extent the location of work (i.e., I am open to mutually agreeable balances of on-site vs. off-site work where appropriate). The terms of appointment are typical -- one year initially, renewable for up to two more years; funding is in place. For applicants looking to establish new funding, it is worth knowing that it is possible at UCI for Postdoctoral scholars to lead their own proposals and that positions beyond Project Scientist exist in special cases.
Our campus is nestled in Southern California between Los Angeles and San Diego, in the heart of Orange County. It is a pleasant place to live, with a Mediterranean climate and good access to such attraction as: beaches (e.g., Crystal Cove and Laguna Beach), the San Bernardino mountains and forests, the Mojave desert and Los Angeles. The Earth System Science Department at UC Irvine is a highly interdisciplinary and modern research environment comprising ~ 25 faculty with expertise across many components of the Earth System, including atmospheric physics, land surface processes, climate dynamics, terrestrial and marine biogeochemical cycles, ice sheets, and human systems. The University of California is known for offering competitive retirement savings, health and family benefits, and has a strong institutional commitment to inclusive excellence and diversity.
If you are interested in any of these positions, please send me a brief e-mail indicating which one(s) [and why] along with your CV. I can be reached at firstname.lastname@example.org.
Dept of Earth System Sciences
University of California, Irvine
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