Sort by
Refine Your Search
-
and pain research Required Qualifications: PhD (or equivalent) in epidemiology, health data science, biomedical informatics, biostatistics, public health, or a related field. Demonstrated experience
-
chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
-
& Brian Hargreaves. Partial list of applicable skills: Expertise in MRI physics Experience with raw MRI data management Experience with MRI reconstruction Clinical studies: data collection / analysis Pulse
-
meetings Key Responsibilities: Development and implementation of study protocols Participant recruitment and collection of participant and laboratory data Statistical analysis of data Authorship
-
. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods
-
psychology or pediatric anesthesiology. In addition to core research activities, the fellowship emphasizes capacity-building in grant writing, manuscript preparation, advanced data analysis techniques, and the
-
. Electrophysiology and MRI Data Analysis of Patients with Lennox-Gastaut Syndrome About Us: Stanford Pediatric Epilepsy Research is at the forefront of research in neuroscience, focusing on understanding complex
-
Posted on Sat, 11/09/2024 - 11:35 Important Info Faculty Sponsor (Last, First Name): Gardner, Christopher Other Mentor(s) if Applicable: Clarke, Shoa, MD, PhD; Follis, Shawna, PhD, MS; Henriksen
-
protocols. Provide hands-on technical/operational support for preclinical FLASH irradiation experiments of multiple users in collaborating laboratories Contribute to data analysis, manuscript preparation, and
-
. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth