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If you are interested in any of these topics, you are welcome to contact the Professor responsible for the position. Also, it is recommended to mention your interest in the application form, among your scientific interests and in your statement of objectives. |
| Research Area | Topic | Professor | Description | Deadline |
| Applied and computational mathematics | Advanced adaptive numerical methods for fully nonlinear equations | Prof. Marco Picasso | The goal is to efficiently solve several, non-smooth, fully nonlinear equations using adaptive algorithms or machine learning techniques. We explore various aspects of the approximation of the Monge-Ampère equation including (but not limited to): • adaptive mesh refinement with optimal error estimates based on finite element formulation. • solution of the parametric Monge-Ampère equation using a PINN approach. • solution of higher dimensional fully nonlinear equations using deep neural networks. • inverse problems with the Monge-Ampère equation as a constraint. The PhD candidate will work under the supervision of both Prof. Alexandre Caboussat (Haute école de gestion de Genève (HES-SO), and Prof. Marco Picasso (MATH, EPFL). The position is subject to admission to EPFL doctoral program of mathematics. For more information, please contact [email protected] and [email protected]. | April 15, 2023 |
| Research Area | Topic | Professor | Description | Deadline |
| Applied and computational mathematics | Randomized numerical linear algebra | Prof. Daniel Kressner | The project is concerned with the development and analysis of randomized algorithms for solving large-scale linear algebra problems. A particular emphasis is on low-rank matrix and tensor approximation. For more information, please contact [email protected] | April 15, 2023 |
| Research Area | Topic | Professor | Description | Deadline |
| Applied and computational mathematics | Randomized linear algebra for data analysis and complex simulations | Prof. Laura Grigori | In the context of the ERC Synergy project EMC2, the focus of this PhD will be on using randomization techniques for solving large scale linear algebra problems arising in data analysis and complex simulations. More information here. | April 15, 2023 |
| Research Area | Topic | Professor | Description | Deadline |
| Applied and computational mathematics | Numerical methods for optimization under uncertainty | Prof. Fabio Nobile | A PhD position is available in the CSQI lab on the development of efficient numerical methods for optimization under uncertainty and stochastic optimal control problems with applications in mechanical engineering and the energy sector. For more information, please contact [email protected] | April 15, 2023 |