Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- Germany
- United Kingdom
- Portugal
- Sweden
- Spain
- Norway
- Netherlands
- Japan
- Belgium
- Hong Kong
- Italy
- Luxembourg
- Switzerland
- Denmark
- Poland
- Singapore
- United Arab Emirates
- Brazil
- Ireland
- Finland
- Lithuania
- Saudi Arabia
- Vietnam
- Austria
- Canada
- Cyprus
- Czech
- Estonia
- Europe
- Malta
- Worldwide
- 23 more »
- « less
-
Program
-
Field
-
), Multilayer Perceptron (MLP), Autoencoders, Convolutional Neural Networks (CNNs), and Kolmogorov–Arnold Networks (KANs). Desirable knowledge of Gradient Boosting models such as HistGBM, LightGBM, and XGBoost
-
and conferences related to the topics of the position Expertise in one or more of the following areas: Wireless and satellite communications AI/ML for dynamic networks including Graph Neural Networks
-
epilepsies. They use a range of advanced genomic techniques including single-cell and spatial multiomic evaluation of epilepsy surgical tissue as well as iPSC-derived neural cultures and mouse models
-
in a research environment a plus General languages (preferred): C++, Python, MATLAB CUDA (strongly preferred) Machine learning knowledge. e.g. logistic regression, SVM, neural network models Basic
-
of gestation. However, the cortical structures underlying these processes remain unknown. Does this capacity rely solely on auditory networks, or does it also involve sensorimotor regions, as observed in adults
-
of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes that focus
-
for quantized and pruned neural networks, creation of quantized and pruned demonstration models, reproduction of state of the art, experiments in heterogeneous quantization Depending on expertise
-
, focusing on AI- based quantitative imaging of human hemodynamics, as well as neural network models of nonlinear ultrasound for imaging and quantitative tissue property estimation. The outcome of
-
, focusing on AI- based quantitative imaging of human hemodynamics, as well as neural network models of nonlinear ultrasound for imaging and quantitative tissue property estimation. The outcome of
-
transfer, fluid–solid interactions, and pressure drop in complex thermal structures. Design and train physics-guided surrogate models (e.g. neural networks with embedded physical constraints) for rapid