Sort by
Refine Your Search
-
constructs and within-person change, as well as spoken narrative data. The overarching goal is to characterize longitudinal trajectories of core computational constructs (e.g., reward learning, decision-making
-
and deep learning methods for large-scale genomic, clinical, and imaging biobank data, with stable multi-year NIH support. The Zhi Laboratory has a sustained track record of methods development
-
scientists, and collaborators at academic and health-system sites nationally and internationally. The position is supported primarily through the DISCOVER-AI initiative, a three-year project within
-
academic research career within a collaborative and mentorship-oriented environment. The research environment is highly collaborative and publication-oriented, with opportunities for trainees to lead
-
collaborative work, as evidenced by publications or preprints. Enthusiasm for learning neuroimmune biology is essential; prior formal immunology training is not required. Mentoring, training, and collaborations
-
, design and analysis of virus-derived RNA libraries, and development of machine learning models for detecting functional elements in viral metagenomic datasets. This project is a collaboration with the
-
The postdoctoral associate will be embedded in a collaborative research environment that brings together expertise in functional genomics, regulatory genomics, machine learning, population genetics, and human
-
evolutionarily conserved structured RNAs and candidate mammalian riboswitches from large genomics and transcriptomics datasets. The position will involve close collaboration with experimental scientists who will
-
studies how the infant brain learns about the social world and how early-life experience shapes neural circuits with long-term consequences for learning, attachment, and mental health. Our work focuses on
-
-scale human datasets. You will: - Build and apply machine learning and deep learning models to multi-scale (cells, brains, patients), multi-modal (omics, biosensor data, vision, electronic health data