Marie Skłodowska-Curie Postdoctoral Fellowships 2024.
Young researchers in mathematical control theory are invited to apply for Marie Skłodowska-Curie Postdoctoral Fellowships 2023. We offer candidates the opportunity to jointly prepare an original and personalized project proposal and, once we get the funding, pursue a two-year research project in control theory under the supervision of prof. Martin Lazar.
A special attention within the project will be given to the professional development and training of the candidate. In particular, he/she will have the opportunity to participate in ongoing research projects, to benefit from an international research network of the supervisor and his collaborators, to disseminate his/her results, and to get trained in specialized schools and workshops.
Eligible candidates must hold a Ph.D., must have a maximum of 8 years of research experience from the time the Ph.D. was awarded, and cannot have lived or worked in Croatia for 12 months or more over the past three years.
The details on the programme can be found on
How to apply:
Please send an application by email to email@example.com including following documents:
- List of publications
- Brief description of the project idea (see the template here)
(a project proposal will be made jointly by the researcher and the host institution).
Former Postdoctoral Researchers
Cristhian Montoya, 2021, a postdoctoral researcher of Applied Mathematics, at Department of Electrical Engineering and Computing in the University of Dubrovnik, under the supervision of Prof. Martin Lazar. Research interest: reduction methods using artificial neural networks for solving parametric time—dependent equations, inverse problems, control theory, numerical analysis and mathematical modeling for partial differential equations. See CV for more.
Jerome Weston, 2018 – 2020, a postdoctoral researcher of Applied Mathematics, at the Department of Electrical Engineering and Computing, University of Dubrovnik, under the supervision of Prof. Martin Lazar.
Research interests: stability control for nonlinear and linear time-varying systems. Specifically, with the use of bounded backstepping and sequential prediction methods. See CV for more.