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DOCC Marie Skłodowska-Curie fellows


Nasser ALKMIM, MSc
Unit of Strength of Materials and Structural Analysis
Research area(s): Computational mechanics
Thesis: Efficient numerical methods for solving multifield problems in structural engineering
Main supervisor: Univ.-Prof. Dr. Günter Hofstetter

More about Nasser »

Nasser Alkmim comes from the capital of Brazil. He completed his M.Sc. in Structural Engineering from the University of Brasília in 2019. His favorite Mahler symphony is the third and he likes to lift heavy weights. Nasser's research interest is computational mechanics, particularly focused on the simulation of materials considering microstructure phenomena. His master's thesis was on multiscale analysis. Nasser is also interested in programming and the implementation aspects of numerical procedures.


Giorgios BAGIATIS, MSc
Department of Atmospheric and Cryospheric Sciences
Research area(s):   Atmospherical fluid dynamics
Large eddy simulation and direct numerical simulation in atmospheric boundary layer
Main supervisor: Univ.-Prof. Dr. Mathias Rotach

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Giorgos Bagiatis from Thessaloniki, Greece obtained his MEng degree in Mechanical Engineering from Aristotle University of Thessaloniki, Greece. His thesis was "Optimization of Vertical-Axis Wind Turbines". Giorgos obtained his MSc degree in Computational Fluid Dynamics (CFD) from Cranfield University, United Kingdom. Giorgos' master thesis was "Shock/shock and shock/boundary layer interactions in hypersonic rarefied flows using dsmcFoam+". His academic interests are in the field of fluid dynamics; in particular atmospheric flows, atmospheric boundary layer in complex terrain, turbulence modelling, aerodynamics, numerical methods and various CFD applications.

The preliminary title of Giorgos´ PhD thesis project is "The causes of anisotropy in the inertial subrange and dissipation range over complex terrain using Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES)". In this project, he investigates the lower part of the Atmospheric Boundary Layer (ABL), so the simulations aim to explain what is happening in the inertial sub-layer (and roughness sub-layer) over flat, rough and complex terrain, as well as under neutral, stable and unstable stratification. The main goal is to check the validity of local isotropy according to Kolmogorov's theory (plot energy and velocity spectra, 2nd and 3rd order structure-function) and if it is violated find out the possible causes (shear or convection) and how they act on the isotropy of turbulence. Furthermore, the DNS study aims to resolve the smallest scales of the flow and provide an analytical solution of the dissipation rate of turbulent kinetic energy (comparison with estimated values from spectra). 


Theoretical High Energy Astrophysics
Research area(s): Astrophysics and space science
Thesis: Multimessenger astrophysics of high-energy sources
Main supervisor:  Univ.-Prof. Dr. Anita Reimer

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Margot, a french astrophysicist, comes from Nantes, a city in the North-West coast of France where she did her physics bachelor studies. She moved south to Toulouse where she got her master degree in astrophysics and space sciences. She enjoys learning, obviously, but in her free time also likes going out with friends, enjoying the sun (if it's at the beach it's even better!) and playing piano.

Margot´s PhD thesis is about modelling the multi-messenger emission from low-luminosity Active Galactic Nuclei. In short, she is studying the jets coming from active regions close to super-massive black holes. By modelling the different populations of messengers (they change depending on the model) coming from these jets, we can learn information about the origin of the most energetic particles that are detected on Earth. This also allows us to better understand the physics happening in such extreme environments, where general relativity rules over the classical laws of physics.



Unit of Applied Mechanics
Research area(s):  Structural Dynamics, Structural Identification and Monitoring and Stochastic Mechanics
Thesis:  Smart control of earthquake excited non-linear base-isolation systems
Main supervisor: Univ.-Prof. Dr. Christoph Adam

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Miriam Chillemi is from Italy. She got her Bachelor’s Degree in Civil and Environmental Engineering at the University of Catania and then her Master’s Degree in Building Engineering at the University of Palermo. Over the course of her master’s studies Miriam became truly passionate about structural dynamics, structural identification and monitoring and stochastic mechanics, which led her here to the University of Innsbruck, working with Professor Christoph Adam and his research group.

Her research concerns passive vibration control systems for civil engineering applications. In particular, she is working on novel applications for a mechanical device called “inerter” which has already been successfully used in the automotive sector. Inerters are comparatively recent additions to the arsenal of civil engineers and the main purpose of her project is to study the applicability and efficiency of this device by exploring new configurations in a civil engineering context suitable for real-life applications and, consequently, finding optimized parameters to improve and expand the analytical model of the system. The ultimate goal is to construct a small-scale model as a proof of concept to experimentally validate the analytical model as this is an area which has not been extensively studied.


Thi Tam DANG (v. Yukiko), MSc
Department of Mathematics
Research area(s): Partial differential equations and numerical analysis
Thesis: Exponential integrators for nonlinear advection-diffusion problems
Main supervisor: Univ.-Prof. Dr. Alexander Ostermann

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Thi Tam Dang (Vietnamese name) or Yukiko Masaki (Japanese name) comes from Vietnam. Yukiko has studied for her master's program in France and Italy. Her interest in studying mathematics in the field of partial differential equations and numerical analysis for partial differential equations.

In the doctoral thesis, she will concentrate on studying the problem of order reduction and will propose a new method to overcome the reduction of order for advection-diffusion equations in general cases. Furthermore, Yukiko will pay attention to the discussion on possible extensions of the results to boundary layers and absorbing boundary conditions. More generally, the idea of splitting methods when applied to the systems of coupled ordinary and partial differential equations with an additional constraint is an interesting perspective. This is still a big challenging task: order reduction usually occurs and it is not easier to modify the method to attain the desired order. In this thesis, she will investigate this issue further to derive a new approach that correctly the order of convergence.



Department of Computer Science
Research area(s):  Deep learning methods for augmenting numerical solvers for partial differential equations
Thesis:  Acceleration of physically-based simulations with convolutional neural networks
 Main supervisor:  Univ.-Prof. Dr. Matthias Harders

More about Viktor »

Viktor Daropoulos is currently a PhD student at the University of Innsbruck, Austria. He completed his diploma in Electrical & Computer Engineering in 2014 at the Aristotle University of Thessaloniki, Greece, and gained a master's degree in Computer Science in 2019 from Saarland University, Germany.

In mid 2020, he joined the Interactive Graphics and Simulation Group (IGS). His current research is focused on using deep  learning methods for augmenting numerical solvers for partial differential equations in order to create fast and effective physically based simulations.



Institute for Ion Physics and Applied Physics
Research area(s): Two-dimensional layered materials, light-matter interaction, atomic and molecular systems 
Thesis: Multicenter growth processes of nano-clusters in suprafluid Helium 
Main supervisor:
Univ.-Prof. Dr. Paul Scheier

More about Elham »

Elham Ghavidel comes from Iran. She completed her bachelor’s degree in engineering physics and master’s in nanophysics at the Plasma Physics Research Center, Science and Research branch of Islamic Azad University of Tehran, Iran. In general, her research interests lie in the field of two-dimensional layered materials, light-matter interaction, atomic and molecular systems. 

Currently, Elham is a PhD candidate at the Institute for Ion Physics and Applied Physics, University of Innsbruck. She is studying the growth processes of Nano-clusters in superfluid Helium and simulating these processes via quantum chemistry calculations.

 goeppel_simon_web.jpg Simon GÖPPEL, Msc
Department of Mathematics
Research area(s): Inverse Problems 
Deep Learning for incomplete models and missing data in inverse problems
First supervisor: Univ.-Prof. Dr. Markus Haltmeier

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Simon comes from a small town near Nürnberg, Germany. He studied mathematics at the University of Applied Sciences in Regensburg and after almost two years working as a Data Scientist, he is happy to be back at the University and finally pursue his PhD degree.

The project he is working on deals with inverse problems and in particular situations where the underlying model is not fully described or measurements are not complete. For example in computed tomography, one is often faced with situations, where dynamic behaviour of the human body is not incorporated in the mathematical model, or measurements can not be taken at full angular range. In his thesis, he tries to develop refined reconstruction strategies, which also employ new methods from deep learning.


Samadrita KARMAKAR, MSc
Unit of Material Technology Innsbruck
Research area(s):  Numerical Methods, specially Finite Element Methods 
Multiscale Framework for Hierarchically-Organized Protective Materials
Main supervisor: Univ.-Prof. Dr. Roman Lackner

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Samadrita is from Kolkata, the capital city in India's state of West Bengal. He holds an Erasmus Mundus MSc in Computational Mechanics from UPC, Barcelona, Spain and ECN, Nantes, France. Samadritas interest is in numerical methods, specially finite element method, it's different applications and variations.

Samadrita is part of the project "Multiscale Framework for Hierarchically-Organized Protective Materials". It's goal is to simulate processes involving large deformations during indentation experiments, impaction of protective materials and compaction of power like material during green body production. The research plan is to use Particle Finite Element (PFEM) to deal with expected Large Deformations and use Micromechanics based models to deal with the material behaviour. The hope is that the research will contribute in enhancing PFEM algorithms when used in combination with micromechanics based material models.

 kaur_harpreet_web.jpg Harpreet KAUR, MSc
Institute for Theoretical Physics
Research area(s):  Active Particles, Machine learning and Target search strategies 
Characterizing rare events in soft condensed matter via emerging computational techniques 
Main supervisor:
Univ.-Prof. Dr. Thomas Franosch

More about Harpreet »

Harpreet is a Ph.D. candidate at University of Innsbruck in the bio and nano physics Group advised by Prof. Thomas Franosch. She completed her master’s in Applied Physics (2020) from Amity University, Noida India. Along with her master’s she has had the pleasure of working as a research intern at the Indian Institute of Science (IISc) Bangalore and IIT Delhi. Harpreet´s current research interests include: Active Particles, Machine learning and Target search strategies. Beyond the world of research, she likes to do painting (click the below link) and singing: https://fileshare.uibk.ac.at/d/b085b9489a414807b3b6

The title of Harpreet's Ph.D. project is “Characterizing rare events in soft condensed matter via emerging computational techniques”. The goal of her research is to study how microscopic particles find specific targets (food/shelter) intelligently by learning from own’s actions. In the community of active particles optimal planning path and target search strategies are one of the most central problems. She and her group determine these target-search strategies by making use of machine learning technique, particularly reinforcement learning. The project aims to establish an inclusive characterization of the target search strategies learned by microswimmers. Furthermore, the project faces some of the most important open questions regarding target search performed by active particles.



Stefan-Tiberiu KIS, MSc
Institute for Astro- and Particle Physics
Research area(s): Astrophysics: transport of cosmic rays, core-collapse supernova, accretion disks
Thesis: Modelling of cosmic-ray transport and gamma ray emission in a dynamical galaxy
Main supervisor:
assoz. prof. Dr. Ralf Kissmann

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Stefan hails from one of the cities known as "Little Vienna", Timisoara, in western Romania. He graduated from the West University of Timisoara in the field of theoretical physics, with accents on quantum field theory and computational physics. His main research interests go around astrophysical phenomena: transport of cosmic rays, core-collapse supernova, accretion disks.

Stefans thesis project pertains to validating an already existing cosmic-ray transport code, PICARD, started by his doctoral supervisor assoz. Prof. Dr. Ralf Kissmann. Numerical codes that are written to solve the cosmic-ray transport equation lack a solid benchmark to test their code against and the main goal is to create or compile a list of tests for these codes. Another aspect of the thesis is including time evolution to the PICARD code. The motivation for this is that at some point in time a cosmic-ray source appears and after thousands of years it disappears.



Alexander MORIGGL, MSc
Department of Mathematics
Research area(s):  Vlasov-Poisson equation 
Semi-Lagrangian plasma simulation on modern computer architectures 
Main supervisor:
assoz. Prof. Lukas Einkemmer

More about Alexander »

Alexander comes from South-Tirol, Italy. He studied Mathematics at the University of Verona.

The title of his thesis project is „Semi-Lagrangian plasma simulation on modern computer architectures“. In particular, he and his group are solving the Vlasov-Poisson equation efficiently on graphic processing units (GPUs) and also on large GPU clusters. They achieve this by using the semi-Lagrangian discontinuous Galerkin method (SLDG), which follows the characteristics backward in time.

 pomarici_nancy_web.jpg Nancy POMARICI, Dott.ssa
Institute of General, Inorganic and Theoretical Chemistry
Research area(s): C omputational technique applied to monoclonal antibodies 
Thesis: Machine Learning in Analysis of Molecular Dynamics Simulations   
supervisor: Univ.-Prof. Dr. Klaus Liedl

More about Nancy »

Nancy Pomarici comes from Italy. Her hometown is Matera, but she moved to Pavia to study Chemistry and Pharmaceutical Technology. Nancy already had spent a few months in Innsbruck with the Erasmus Traineeship program to study for her master thesis in theoretical chemistry.

Her master thesis project was about computational technique applied to monoclonal antibodies, in order to study the conformational ensemble that they can adopt in solution. In her doctoral studies, she continues to investigate the dynamics of these molecules. Monoclonal antibodies are emerging as promising drugs, since they have the ability to specifically bind several types of pathogens. Molecular dynamics simulations allow the investigation of their biophysical properties, like stability or hydrophobicity. Consequently, it may be possible to make suggestions for modifications, in order to improve their therapeutical usage.


Institute for Ion Physics and Applied Physics
Research area(s): Computational science - atomistic modelling, quantum chemical calculations and in applications of machine learning 
Thesis: Dynamics of molecules in the plasma/surface region
First supervisor: a.o. Univ.-Prof. Dr. Michael Probst

More about Shokirbek »

Shokirbek was born and grew up in Tashkent, Uzbekistan. He graduated as Master of Science at the Kazan National Research Technological University (Russian Federation). His research interests are in computational science, in particular atomistic modelling with molecular dynamics and Monte Carlo methods, quantum chemical calculations and in applications of machine learning.

The main goal of his thesis project is the development of machine learned potential energy surfaces that can accurately predict interactions at interfaces and the application of them in simulations to model material properties of plasma facing components This typically includes: ab initio molecular dynamics calculations to generate and augment training data; fitting a neural network potential to them; generating a representative sample of the possible events and reactions using classical molecular dynamic simulations based on the neural network potential; and an analysis of the trajectories to understand the processes in the materials and to generalize them.


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847476.

Co-funded by the European Union

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