Sort by
Refine Your Search
-
to statistical computing, Bayesian modeling, causal inference, clinical trials and analysis of complex large-scale data such as omics data, wearable tech, and electronic health record, with specific preference
-
to statistical computing, Bayesian modeling, causal inference, clinical trials and analysis of complex large-scale data such as omics data, wearable tech, and electronic health record, with specific preference
-
structure theory (especially large-scale computation of complex materials and structures). Physical Demands Salary Range $52,500 - $57,500 Additional Salary Information The salary range reflects our good
-
Posting Details Position Information Fiscal Year 2023-2024 Position Title Academic Scholar – Clinical Assistant or Associate Professor, Pediatrician, Division of Developmental Pediatrics and
-
related to Earth Science, Polar Science, Glaciology, Climate Science or Civil Engineering Preferred Qualifications experience in data compilation and analysis experience with large dataset (observations
-
opportunities to work with state-of-the-art natural language processing, large language models (LLMs), computer vision models, speech models, time series models, and many other related machine learning models
-
learning (including big data analytics and adversarial machine learning), natural language processing (audio-visual multimodal understanding), autonomous systems (such as driverless cars), human-robot
-
(including video analysis and 3D reconstruction), machine learning (including big data analytics and adversarial machine learning), natural language processing (audio-visual multimodal understanding
-
Artificial Intelligence and Robotic Systems, including computer vision (including video analysis and 3D reconstruction), machine learning (including big data analytics and adversarial machine learning
-
(including video analysis and 3D reconstruction), machine learning (including big data analytics and adversarial machine learning), natural language processing (audio-visual multimodal understanding