-
typologically diverse languages Creating self-supervised learning algorithms that can assess phonological development and speech complexity in children from birth through age 6, with applications to both typical
-
Models with Algorithmic Reasoning Tasks We are seeking a postdoctoral researcher to contribute to our lab’s mission of aligning machine learning (ML) models with algorithmic reasoning tasks. Our goal is to
-
together experts in systems neuroscience, AI, and engineering. This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a
-
. This work involves developing novel techniques, algorithms, and software packages that enable more robust and scalable approaches to cybersecurity using AI-based techniques. In addition to technical
-
into tangible products. Critically, this work will generate a large open-source dataset of child-created games that can inform future designs of educational games and AI algorithms. The postdoctoral fellow will
-
will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
-
systems. Includes establishing medical reasoning benchmarks and automated / scalable evaluation methods. Developing recommender algorithms to predict specialty care with large-language model based user
-
. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will involve both method