Master Thesis Opportunities at CST

NameContact Email Research themes KTH Profile URL Theme 1 Theme 2 Theme 3 Further info Christopher Peters chpeters@kth.se Virtual characters and crowds Procedural graphics generation Game technologies https://www.kth.se/profile/chpeters Link¶

Stefano Markidis markidis@kth.se Performance Modeling and Characterization Physics-Informed Machine Learning Quantum Computing Applications https://www.kth.se/profile/markidisLink Tino Weinkauf weinkauf@kth.se Visualization in general Feature-based Data Analysis Topology, Trees, Graphs https://www.kth.se/profile/weinkauf Robert Lindroos rlindr@kth.se Computational Neuroscience Machine learning Synaptic plasticity - learning https://www.kth.se/profile/rlindr?l=enLink Arvind Kumar arvkumar@kth.se Markerles tracking to detect future epilepsy in infants Analysis of brain activity data Computational modelling of biological neural networks https://www.kth.se/profile/arvindkuLink Ivy Peng bopeng@kth.se Heterogeneous parallel computing Memory-centric Computing Converged Cloud and HPC system https://www.kth.se/profile/bopengLink Jörg Conradt conr@kth.se Object detection with biological vision Accelerated biological learning on GPUs Biological neurons in embedded systems https://www.kth.se/profile/conr Pawel Herman paherman@kth.se Brain-like computing Computational neural network modelling of brain cognitive function Brain-computer interfaces https://www.kth.se/profile/paherman Martin Rehn rehn@kth.se Computational Neuroscience Machine learning Quantitative finance https://www.kth.se/profile/rehn/ Golnaz Taheri golnazt@kth.se Computational biology for cancer detection Machine learning Deep learning for drug intraction prediction https://www.kth.se/profile/golnazt Olivia Eriksson olivia@kth.se Model extension and model selection of a synaptic plasticity model Structural Identifiability for models of the brain https://www.kth.se/profile/olivia