Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Pennsylvania State University
- Delft University of Technology (TU Delft)
- Aarhus University
- NEW YORK UNIVERSITY ABU DHABI
- New York University
- Northeastern University
- University of Miami
- University of Minnesota
- University of Oxford
- University of Oxford;
- AALTO UNIVERSITY
- Argonne
- Centro de Investigación en Matemáticas
- Chalmers University of Technology
- Chinese Academy of Sciences
- Cornell University
- Duke University
- Durham University
- European Space Agency
- GFZ Helmholtz-Zentrum für Geoforschung
- George Washington University
- Grenoble INP - Institute of Engineering
- Helmholtz Association of German Research Centres
- ICN2
- Indiana University
- Inria, the French national research institute for the digital sciences
- Instituto Superior Técnico
- Johns Hopkins University
- King Abdullah University of Science and Technology
- National Aeronautics and Space Administration (NASA)
- National Energy Technology Laboratory (NETL)
- Princeton University
- SciLifeLab
- St Jude Children's Research Hospital
- Stony Brook University
- Texas A&M AgriLife Extension
- Télécom Paris
- Umeå University
- Universidad Complutense de Madrid
- University of Caen Normandie
- University of Chinese Academy of Sciences (UCAS)
- University of Graz
- University of Massachusetts Chan Medical School
- 33 more »
- « less
-
Field
-
& Geometric Models, Low Effective-dimensional Learning Models, Implicit Regularization, and Reinforcement Learning through Stochastic Control (a brief description of each these is as follows (additional details
-
to scientific computing and other scientific domains. Candidates with strong backgrounds in stochastic analysis, numerical analysis, sampling methods, optimization, scientific computing, or related areas
-
Intelligence and Machine Learning, Computational Statistics, Random Matrices, Free Probability, Stochastic Control, Mathematical Finance, Stochastic Partial Differential Equations, Markov Processes, Branching
-
for stochastic, distributionally robust, and mixed-integer nonlinear optimization problems. The successful candidate will conduct research at the intersection of stochastic programming, optimization under decision
-
vibration control, with demonstrated expertise in stochastic dynamics or random vibration, computational modeling, and experimental validation of mechanical systems. The successful candidate will work closely
-
optimization models for electric vehicle fleet charging planning. Activities: • Apply operations research methods (linear and mixed-integer programming, dynamic optimization, stochastic optimization) • Integrate
-
systems, numerical analysis, stochastic problems and stochastic analysis, graph theory and applications, mathematical biology, financial mathematics and mathematical approaches to signal analysis
-
groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative projects with other group members and our
-
theoretically, in tight collaboration with experimental groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative
-
Stochastic Processes. Expertise in numerical simulations (with Matlab or Python) as well as basic knowledge of neural nets will be valued but not required. Additional Information Applicants must complete