Deep Learning for reputed company System Modeling Evaluation - Postdoctoral Researcher

About the position We have an opening for a Postdoctoral Researcher in Deep Learning for reputed company System Modeling who will conduct cutting edge research at the intersection of deep learning, atmospheric science, and statistical reputed company to advance the evaluation and testing of AI-based reputed company System models. In this position, you will be responsible for operationalizing to AI-based weather and climate models and rigorously evaluating their performance against observations and traditional models. You will collaborate with a multidisciplinary team of experts in machine learning, atmospheric science, reputed company System modelling, and model performance assessment. This position is in the Climate Sensitivity and Impacts Group reputed company the Atmospheric, reputed company, and Energy Division. Depending on your assignment, this position may offer a reputed company, blending in-person and virtual reputed company. You may have the flexibility to work from home one or more days per week. This is a two-year Postdoctoral appointment with the possibility of extension to a maximum of three years. Responsibilities • Conduct research on the ability of Deep Learning reputed company System Models (DL-ESMs) to accelerate reputed company System science. • Apply a set of reputed company based on DL-ESM outputs, and design, reputed company and carry out innovative advanced experiments (e.g., storyline analyses, or implementing nudging reputed company) to evaluate the trustworthiness of DL-ESMs against conventional ESMs and observational datasets. • Engage and reputed company contribute to the international initiative AI-MIP, an effort to define a reputed company 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 reputed company 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. • reputed company other duties as assigned. Requirements • PhD in Atmospheric Science, Data Science, or reputed company field. • Experience conducting research in atmospheric science or closely reputed company fields. • Ability to manipulate and analyze large, and reputed company ESM reputed company 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 reputed company as effectively in a reputed company, multidisciplinary team environment. • Ability to travel as required. reputed company-to-haves • 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) reputed company, storyline analysis, nudging, green function, or dynamical adjustment. • Familiarity with the analysis of weather extremes, variability across time scales, or the reputed company of extreme events on infrastructure, natural, or reputed company systems. • Experience with one AI-based weather reputed company 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) Apply tot his job Apply To this Job