Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
Areas: Financial Mathematics, Data Science, Optimization, Statistics Appl Deadline: (posted 2026/02/27 05:00 AM UnitedKingdomTime, listed until 2027/02/25 04:59 AM UnitedKingdomTime) Position Description
-
Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 12 days ago
technologies to handle the growing datasets. Candidates should have experience with the handling of animal data as well as deep knowledge in mathematical modelling and optimization. Thus, a master's degree in
-
use classical methods of analysis and synthesis. However, in the case of large systems, this type of approach will generally lead to very large optimization problems. A second strategy is to describe
-
systems, mathematical optimization, machine learning, or data science. Montana State University is a land-grant institution committed to achievement in research. The Department of Mathematical Sciences has
-
] Subject Areas: mathematical modeling, statistics, machine learning, data-driven modeling, dynamical systems, optimization Appl Deadline: 2026/04/01 04:59 AM UnitedKingdomTime (posted 2026/02/19 05:00 AM
-
Department of Applied Mathematics Assistant Professor in Optimization and Operations Research / Statistics and Data Science / Financial Mathematics / Engineering and Computational Mathematics
-
10 Apr 2026 Job Information Organisation/Company Hewlett Packard Enterprise Research Field Engineering » Electrical engineering Computer science Mathematics Physics Researcher Profile Recognised
-
of mathematics, to develop innovative application-oriented mathematics with a focus on data-driven modelling, simulation, and optimization, and to open new mathematical thinking spaces. MATH+ is supported by
-
, China [map ] Subject Areas: Computational Mathematics, Applied Mathematics, Artificial Intelligence, Numerical Analysis, Optimization, Statistics Appl Deadline: none (posted 2024/08/02 05:00 AM
-
: The ideal candidate should have: * Knowledge of machine learning, especially neural networks or graph neural network or federated learning. * Strong mathematical and algorithmic background (optimization