Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- University of Oslo
- Harvard University
- Humboldt-Universität zu Berlin
- INESC ID
- Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial
- Northeastern University
- Łukasiewicz PORT
- Christian-Albrechts-Universitaet zu Kiel
- FCiências.ID
- Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S)
- King Abdullah University of Science and Technology
- NOVA.id.FCT- Associação para a Inovação de Desenvolvimento da FCT
- Nanyang Technological University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- SUNY University at Buffalo
- Singapore University of Technology & Design
- The University of Memphis
- University of British Columbia
- University of Nottingham
- 9 more »
- « less
-
Field
-
who are interested in these or related fields, particularly those who may bring a new technology or perspective to bear on the work in the lab. Familiarity with neural networks and/or primate
-
within a Research Infrastructure? No Offer Description Work Plan Study and application of methods for extracting understandable concepts and inducing logic-based theories from neural networks. Study 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
-
Charité–Universitätsmedizin Berlin (Dr. Rosanna Sammons); for further information, see https://www.sfb1315.de/ - development of network models of the CA3 region of the hippocampus - investigation
-
candidate will work with open available datasets obtained in rodents and unique datasets of neural activity. Your primary focus will be to design new learning frameworks and neural network architectures
-
programming (MATLAB and Python); knowledge of data processing; experience in mathematical modelling, especially dynamic systems and neural networks; previous experience with burned area algorithms. Contracting
-
desirable. Familiarity with explainable AI, causal inference, or biologically inspired neural networks, as well as experience collaborating with experimental laboratories, will be considered strong assets
-
Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 1 month ago
of numerical simulations and digital twins. By using advanced machine learning methods, such as Physics-Informed Neural Networks (PINNs) and Variational Physics-Informed Neural Networks (vPINNs), the project
-
research community in exploring near-analog biologic brain inspired solutions to reduce power consumption in neural networks. In this project you will be involved in a collaborative effort investigating
-
, to test the fault-ride-through ability of the converter. Expected Results A neural network structure trained on the limited dataset DT data with high-accuracy impedance estimation under different operating