10 bayesian-inference-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" positions at University of Michigan in United States
Sort by
Refine Your Search
-
Category
-
Field
-
will play an important role in research development and implementation, data collection and organization, and data analysis, particularly in the context of causal inference in epidemiological research
-
learning, path planning, and Bayesian optimization. Plan and perform experiments, oversee research performed by students and research technicians, and mentor and train postdoctoral fellows, graduate students
-
, performing retrospective clinical analyses, and generating statistically robust insights through sophisticated causal inference methodologies. Mission Statement Michigan Medicine improves the health
-
Language Model (LLM) Strong biostatistics knowledge including survival analysis and causal inference Experience with reinforcement learning, agentic AI systems and autonomous decision-making frameworks Data
-
designs and methods, clinical trial methods, Bayesian methods, and developing R packages and scalable algorithms. Opportunities for collaboration across the Department of Biostatistics and the Medical
-
, and Black Holes. We find out how scientists infer their existence and measure their properties from observations of the visible parts of our Universe. This is an online, asynchronous class
-
Proficiency in analytical approaches such as IRT, CFA/EFA, SEM, multivariate regression, causal inference methods (e.g., matching, DiD), and grounded theory or thematic analysis Modes of Work Positions that
-
, analytical procedures for causal inference, and statistical monitoring approaches. In addition, successful candidates will have excellent communication skills and administrative acumen, and the ability to work
-
statistics, statistical tests and statistical inference. Ability to analyze and interpret a wide variety of data using descriptive and inferential statistical methods. Data visualization training and skills
-
. Causal Inference & Predictive Modeling: Contributing to the design and development of predictive models, multivariate explorations, and evaluation of intervention impacts. Decision Support System Design