Deep Learning for Earth System Modeling Evaluation - Postdoctoral Researcher

Lawrence Livermore National Laboratory (LLNL) is seeking a Postdoctoral Researcher in Deep Learning for Earth System Modeling. The role involves conducting research on AI-based Earth System models and collaborating with a multidisciplinary team to evaluate their performance against traditional models and observational data. Responsibilities - Conduct research on the ability of Deep Learning Earth System Models (DL-ESMs) to accelerate Earth System science - Apply a set of standard metrics based on DL-ESM outputs, and design, develop and carry out innovative advanced experiments (e.g., storyline analyses, or implementing nudging methods) to evaluate the trustworthiness of DL-ESMs against conventional ESMs and observational datasets - Engage and actively contribute to the international initiative AI-MIP, an effort to define a standard set of experiments for evaluating and benchmarking state-of-the-art DL-ESMs - Pursue independent research and work closely with colleagues in a multidisciplinary team environment to advance research goals - Prepare comprehensive documentations of findings to guide future users - Publish research results in peer-reviewed scientific or technical journals and present results at external conferences and seminars - Travel as required to coordinate research with collaborators or participate in relevant hackathons - Perform other duties as assigned Skills - PhD in Atmospheric Science, Data Science, or related field - Experience conducting research in atmospheric science or closely related fields - Ability to manipulate and analyze large, and complex ESM output datasets, such as those collected in the Coupled Model Intercomparison Project - Proficient programming skills using Python and demonstrated experience with deep learning frameworks (e.g., PyTorch, TensorFlow) - Experience using high-performance computing environments - Proficient verbal and written communication skills as evidenced by peer reviewed publications and presentations - Ability to work independently as well as effectively in a collaborative, multidisciplinary team environment - Ability to travel as required - Experience developing and applying advanced statistical algorithms or machine learning models for one or more of the following applications: weather forecasting, subseasonal-to-seasonal (S2S) prediction, storyline analysis, nudging, green function, or dynamical adjustment - Familiarity with the analysis of weather extremes, variability across time scales, or the impact of extreme events on infrastructure, natural, or human systems - Experience with one AI-based weather prediction model, for example, NeuralGCM, ACE2, GenCast, WeatherNext 2, is a plus Benefits - Flexible Benefits Package - 401(k) - Relocation Assistance - Education Reimbursement Program - Flexible schedules (*depending on project needs) Company Overview - Lawrence Livermore National Laboratory, a national security laboratory, provides transformational solutions to national security challenges. It was founded in 1952, and is headquartered in Livermore, California, USA, with a workforce of 5001-10000 employees. Its website is http://www.llnl.gov.