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Machine Learning Students' Projects
Our Machine Learning students hold each year a mini-conference presenting the results of their master thesis projects. We invite you to see how ML is applicable in various areas of life. Presentations are in English (as the studies are).
M.Sc. student research scholarship in the NCN SONATA grant "Integrative analysis of single-cell genomics data"
Two Master's degree student scholarships in the project "Integrative analysis of single-cell genomics data" funded by the National Science Centre, Poland (2020/39/D/NZ2/03461). Successful candidates will work on the development of computational methods for analysis of experimental data from single-cell sequencing.
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Results of the competition for a scholarship in the NCN SONATA BIS project "Geometry structures behind tensors"
The MSc scholarships offered in NCN SONATA BIS project "Geometry structures behind tensors" for the academic year 2024/25 were awarded to Jakub Jagiełła and to Weronika Obcowska. Congratulations!
Łukasz Chomienia – public defence of the doctoral dissertation
The remote online public defence of the doctoral dissertation will take place on 30 September 2024 at 10:00 AM .
Title of the dissertation: Partial Differential Equations on Low-Dimensional Structures
Supervisor: Assoc. Prof. Anna Zatorska-Goldstein (University of Warsaw)
The link to the defence meeting will be made available after prior registration by e-mail rnd.matinf@uw.edu.pl. The registration of participants will be open until September 27th, 2024.
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Scholarship in High-Dimensional Geometric Algorithms
There is an opening for a scholarship for 6 months starting from October 2024, under the NCN grant “High-Dimensional Data Processing using Sample Compression and Dimensionality Reduction”, which aims to develop efficient algorithms for processing high-dimensional data using geometric and probabilistic tools. Typical areas involve developing geometric algorithms for processing data in non-Euclidean metrics and more general distance functions, reducing data dimensionality, sample compression schemes, etc.
The principal investigator is dr. Kunal Dutta.