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: Research Support. Carries out independently, under supervision, and in collaboration, designated research tasks and projects, making use of selected methodologies (moderation and mediation, causal inference
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: Research Support. Carries out independently, under supervision, and in collaboration, designated research tasks and projects, making use of selected methodologies (moderation and mediation, causal inference
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optimize machine learning training and inference pipelines for accelerator-based systems Apply systems- and compiler-level optimizations, including: Loop transformations, vectorization, parallelization, and
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. Strong statistical modeling skills, including regression and causal inference methods for observational data. Ability to work independently and collaboratively in interdisciplinary research teams
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data · Demonstrated expertise in causal inference and high-dimensional risk adjustment/predictive modeling · Clear scientific writing and communication, an ability to work both independently and in teams
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knowledge of quantitative methods including causal inference and econometric analyses. Additional Qualifications Master’s degree in statistics, economics, or related quantitative field preferred. Experience
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/deployment. Causal Inference/Experimentation: Knowledge of experimental design, randomization, and causal identification methods. There are no teaching requirements for these open positions. Basic
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such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis of complex systems, networks, and large-scale data Machine learning
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. The IMI is a software tool developed in Professor Daniel Jacob’s Atmospheric Chemistry Modeling Group (ACMG) to infer methane emissions from satellite observations. There is demand from stakeholders
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. Solid training in causal inference, including experimental and quasi-experimental methods. 4. Strong programming skills in Stata and/or R. 5. Ability to work both independently and collaboratively, with