Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- NEW YORK UNIVERSITY ABU DHABI
- SUNY Polytechnic Institute
- Chalmers University of Technology
- Inria, the French national research institute for the digital sciences
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Oak Ridge National Laboratory
- Stony Brook University
- Computer Vision Center
- Delft University of Technology (TU Delft)
- Durham University
- Eindhoven University of Technology (TU/e); today published
- FAPESP - São Paulo Research Foundation
- GFZ Helmholtz-Zentrum für Geoforschung
- Georgia Institute of Technology
- INESC ID
- Institut de Físiques d'Altes Energies (IFAE)
- Institute of Physical Chemistry, Polish Academy of Sciences
- National Aeronautics and Space Administration (NASA)
- SUNY University at Buffalo
- Stanford University
- Technical University of Denmark
- Technical University of Munich
- UNIVERSITY OF SYDNEY
- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- Universitat de Barcelona
- University Miguel Hernandez
- University of Beira Interior
- University of Massachusetts
- University of North Carolina at Chapel Hill
- University of Oxford
- University of Southern California
- University of Southern California (USC)
- University of Southern Denmark
- University of Sydney
- University of Texas at Dallas
- Université Savoie Mont Blanc
- Université côte d'azur
- 28 more »
- « less
-
Field
-
for nutrients, light, temperature, the influence of zooplankton or more generally higher trophic levels, as well as other parameters such as parasitism and allelopathy, if possible. The model can build on
-
parameter space, and using and/or developing agent-based models for the movement and behavior of fish in rivers. Presenting material at conferences, writing research papers for publication, and/or assisting
-
machine learning models that predict soil health and crop performance. The position will exploit datasets integrating biochemical and molecular soil parameters (with a focus on microbiome features from
-
1: Extension of the coverage and performance of the HLA-Epicheck model through the addition of new antigens. This also includes optimizing the values of certain model parameters. Task 2: Evaluation
-
, developing and numerically solving diffusion reaction equations, parameter estimation, machine learning, and sensitivity analysis, with an emphasis in building open-source technologies that benefit the entire
-
descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other
-
determination of inversion parameters. 2. Vp and Vp/Vs tomographic inversion, analysis and interpretation of results (Vp/Vs in relation to Vp and seismicity). 3. Participation in events (workshops, conferences
-
with physics-based models Developing robust and adaptive methods for real-time parameter and state estimation Implementing machine learning approaches that preserve physical constraints while handling
-
of the chemicals on droplet stability. You will be responsible for the following: Implementing AI imaging to analyze high-speed droplet movies. Relating the results to the HLD principle and performing its parameter
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
) algorithms for the identification of unknown BRP model parameters from time-course, single-cell (growth and gene expression) measurements over cell lineages. Develop methods for estimation of unobserved