Sort by
Refine Your Search
-
scientists, and machine learning experts will be an essential and enriching component of the position. Strong candidates will have a background in machine learning and natural language processing (NLP), with a
-
knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required. Record of peer-reviewed publications. Knowledge in one or more of the following areas is
-
, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
-
and patient-reported outcomes; (b) observational research and comparative effectiveness studies; (c) intervention studies; (d) clinical informatics, mobile/electronic health; (e) machine learning
-
from varied sources, and machine learning methodologies. The underlying data are complex and will require sophisticated data management and integration skills. A candidate should have proficiency with
-
and aggression, using optogenetics, in vivo imaging, electrophysiology, and sophisticated machine learning/artificial intelligence analyses of mouse behavior. All projects have translational components
-
. Research Themes and Projects: We are an interdisciplinary research team integrating single-cell and spatial genomics, lineage tracing, synaptic proteomics, functional perturbation screening, and machine
-
/Python coding, next-generation sequencing data interpretation, large-scale data integration, and machine learning. Science: strengthen the ability to formulate hypotheses, design aims to test the
-
join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
-
, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups