This page contains a summary of the ENGAGE PhD projects. The ENGAGE Supervisors are available here.
Summary of the ENGAGE projects
Project 1: Machine learning techniques applied to lattice gauge theories – G. Koutsou, The Cyprus Institute (Cyprus)
Project 2: Computation of the anomalous magnetic moment of the muon using twisted mass fermions – C. Alexandrou, The Cyprus Institute (Cyprus)
Project 3: Variational quantum computer simulations for quantum systems and optimization problems – K. Jansen, Deutsches Elektronen-Synchrotron (Zeuthen)/Humboldt University of Berlin (Germany)
Project 4: Detector Simulation and Jet Clustering for HL-LHC with Quantum Computing – K. Borras, Rheinisch-Westfälische Technische Hochschule Aachen/ Deutsches Elektronen-Synchrotron (Germany)
Project 5: Simulating Lattice Field Theories with Quantum Hardware – K. Jansen, Deutsches Elektronen-Synchrotron (Zeuthen)/Humboldt University of Berlin (Germany)
Project 6: Algorithmic development of tensor networks for High Energy Physics – S. Montangero, University of Padova (Italy)
Project 7: Improving the efficiency and quality of 3D seismic imaging addressing HPC aspects – E. Verschuur, Technical University of Delft (The Netherlands)/The Cyprus Institute (Cyprus)
Project 8: Improving the efficiency and quality of 3D seismic imaging applying ML algorithms – E. Verschuur, Technical University of Delft (The Netherlands)
Project 9: Multiscale computational approaches for wetting on soft surfaces – N. Savva, The Cyprus Institute (Cyprus)
Project 10: Multi-scale simulation methodologies of organic semiconductors for morphology control – V. Harmandaris, The Cyprus Institute (Cyprus)
Project 11: Hierarchical multi-scale modelling of macromolecular systems at interfaces – K. Kremer, Max Planck Institute for Polymer research (Germany)
Project 12: Modelling and basic understanding of natural molecules with surfaces and nanoparticles – V. Harmandaris, The Cyprus Institute (Cyprus)
Project 13: Single-Chain and Collective Structure and Dynamics of Polymer Materials – M. Müller, Georg-August-Universität Göttingen (Germany)
Project 14: Deep learning for 3D Synchrotron X-ray tomography data – M. Nikolaou, The Cyprus Institute (Cyprus)/SESAME (Jordan)
Project 15: Automated interpretation of SR-based XRF and IR spectroscopic data using machine learning approach in archaeological sciences – C. Chrysostomou, The Cyprus Institute (Cyprus)/SESAME (Jordan)
Project 17: Artificial intelligence for operator-intensive coherent X-ray imaging procedures – European Synchrotron Radiation Facility (France)
Project 18: Machine Learning for the Real-Time Analysis of X-Ray Spectroscopic Data – European Synchrotron Radiation Facility (France)
Project 19: Microstructure and texture analysis of x-ray diffraction data using Machine Learning – European Synchrotron Radiation Facility (France)