Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- CNRS
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- NEW YORK UNIVERSITY ABU DHABI
- Rutgers University
- FAPESP - São Paulo Research Foundation
- THE UNIVERSITY OF HONG KONG
- Technical University of Munich
- University of Luxembourg
- VIN UNIVERSITY
- Argonne
- SUNY Polytechnic Institute
- Stony Brook University
- Technical University of Denmark
- University of Oxford
- Chalmers University of Technology
- ETH Zürich
- Oak Ridge National Laboratory
- Princeton University
- University of Oxford;
- University of Washington
- Université Grenoble Alpes
- Université Savoie Mont Blanc
- Aarhus University
- BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
- Baylor College of Medicine
- Biobizkaia Health Research Institute
- Boise State University
- Brno University of Technology, Central European Institute of Technology
- Brookhaven National Laboratory
- Carnegie Mellon University
- Consejo Superior de Investigaciones Científicas
- DIFFER
- Delft University of Technology (TU Delft)
- Duke University
- Ecole Normale Supérieure de Lyon
- Emory University
- Episteme
- Fred Hutchinson Cancer Center
- Graz University of Technology
- IMT Atlantique
- INSERM U1028
- Inria, the French national research institute for the digital sciences
- Instituto Politécnico de Bragança
- Istituto Italiano di Tecnologia
- Karolinska Institutet (KI)
- King Abdullah University of Science and Technology
- Leibniz
- Leiden University
- Los Alamos National Laboratory
- Max Planck Institute for Chemistry, Mainz
- Max Planck Institute of Animal Behavior, Radolfzell / Konstanz
- New York University in Abu Dhabi
- New York University of Abu Dhabi
- Norwegian Meteorological Institute
- Pennsylvania State University
- Purdue University
- RIKEN
- Radboud University Medical Center (Radboudumc)
- Ryerson University
- Sandia National Laboratories
- Stanford University
- Texas A&M University
- The University of Edinburgh;
- Télécom Paris
- UNIVERSITE ANGERS
- UNIVERSITY OF HELSINKI
- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- Universite de Montpellier
- University of Amsterdam (UvA)
- University of California Berkeley
- University of California, Merced
- University of Copenhagen
- University of Florida
- University of Glasgow
- University of Lund
- University of Miami
- University of Minnesota
- University of Southern Denmark
- University of Texas at Arlington
- University of Texas at Dallas
- Université catholique de Louvain
- Uppsala universitet
- 73 more »
- « less
-
Field
-
of research include diagrammatic calculations, quantum Monte Carlo methods, density matrix renormalization group and tensor network states, and artificial intelligence and neural networks, with a particular
-
be found on our lab website: https://www.derosierelab.com/ Salary and benefits: ~€2300 net per month for candidates with less than 2 years post-PhD experience; €2450+ net per month for candidates with
-
), 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
-
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
-
. The work will be primarily computational, focusing on the development of deep neural network model architectures and their training. It will involve extending the preliminary results we have already obtained
-
force fields (MLFFs) that combine state-of-the-art equivariant neural network architectures with robust, well-calibrated uncertainty estimates. These models will enable fully automated active learning in
-
and implement Bayesian graph neural networks and convolutional neural networks as surrogates for high-fidelity biomechanical models Quantify and propagate uncertainty, and develop strategies for model
-
architectures to solve data-driven sensing and control problems related to turbulent atmospheric flows. The work will center around investigation of reinforcement learning and convolutional neural networks
-
artificial intelligence and neural networks, with a particular focus on applying these numerical approaches to quantum many-body systems, such as correlated 2D materials, quantum Moire systems, frustrated