Causal Inference Machine Learning Postdoctoral Jobs in Massachusetts

Applying epidemiologic, econometric, and other methods to strengthen causal inference * Working ... Exploring gender, racial/ethnic, and socioeconomic disparities The Postdoctoral Research Associate ...

Job Summary We have an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for ...

Job Summary We have an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for ...

... causal inference, clinical outcomes assessment, longitudinal modeling, evidence synthesis, precision medicine, and the application of artificial intelligence and machine learning. * Develop and ...

We invite applications for a postdoctoral fellowship in the Department of Community Health Sciences ... causal inference methods, and geriatric health. This position offers a competitive compensation ...

We invite applications for a postdoctoral fellowship in the Department of Community Health Sciences ... causal inference methods, and geriatric health. This position offers a competitive compensation ...

The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods ... data, causal mediation analysis and Mendelian Randomization, polygenic risk scores, and AI ...

The Postdoctoral Associate should expect to work from Cambridge, MA for the duration of the ... causal inference required. Qualitative fieldwork experience is also preferred. 3. Proven record of ...

Design, develop, and evaluate statistical, econometric, and machine learning models where ... Apply causal inference techniques (e.g., uplift modeling, DiD, matched controls) to assess ...

Design, develop, and evaluate statistical, econometric, and machine learning models where ... Apply causal inference techniques (e.g., uplift modeling,DiD, matched controls) to assess ...

... machine learning and advanced statistical methods including supervised/unsupervised learning, ensemble forecasting, causal inference, and predictive modeling to pharmaceutical or life sciences data ...

... causal inference frameworks (e.g., Bayesian networks). * Combine data from wearable sensors (e.g ... Strong understanding of linear models, mixed-effect models, and in general machine learning ...

... causal inference frameworks (e.g., Bayesian networks). * Combine data from wearable sensors (e.g ... Strong understanding of linear models, mixed-effect models, and in general machine learning ...

Position Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A ...

As an AI & ML Engineer, you'll design, deploy, and optimize machine learning systems that drive ... causal inference 3. Optimize model performance for latency, accuracy, and cost across cloud ...

... causal inference frameworks (e.g., Bayesian networks). * Combine data from wearable sensors (e.g ... Strong understanding of linear models, mixed-effect models, and in general machine learning ...

... machine learning, advanced analytics or AI-focused roles • Deep foundation in statistics, experimental design, and causal inference, including the ability to explain methodology choices and ...

We're looking for a Senior Machine Learning Engineer to help build and scale the next generation of ... Strong background in one or more of the following: reinforcement learning, causal inference, LLM ...

... machine learning, advanced analytics or AI-focused roles • Deep foundation in statistics, experimental design, and causal inference, including the ability to explain methodology choices and ...

Strong expertise in statistical modeling, machine learning, and applied analytics * Experience ... Strong understanding of experimentation and measurement (A/B testing, causal inference, multi ...