Student, excited about her awesome thesis.

Theses

Department of Stochastic Simulation and Safety Research for Hydrosystems

Stochastics

We offer theses in different research areas.

Procedure

The theses advertised below are intended to provide pointers for topics of possible final theses at our department. Depending on the language capabilities of the supervisor, the work can usually be carried out in German or English.

Often, we can also tailor the focus specifically for project theses, bachelor theses, research modules and master theses.

If you are interested in one of our topics, but the most suitable work for you is not advertised, feel free to contact us anyway -- you will find a contact to the advertised work in the respective notice board.

Unsolicited applications are also possible at any time. 

Topics

Topic Tags Advisor

Distributional Predictions for Fracture Statistics

uncertainty quantification, machine learning

 Tim Brünnette

Using LSTM+PI3NN for Watersheds in Germany

uncertainty quantification, machine learning

 Tim Brünnette

Data-Regime Uncertainty for Machine-Learned Percentiles

uncertainty quantification, machine learning

 Stefania Scheurer

A LEGO-like Reconfigurable Surrogate Model for Water Pipe Networks

surrogate modeling, GNNs, water pipe networks

 Tong-Chuan Che
Wolfgang Nowak

Applying Deep Learning Models for Hydrological Simulations

hydrological modeling, neural networks

 Sergio Callau Medrano
Modeling of Water Temperature in Drinking Water Supply Pipes

hydrological modeling, numerical simulation, DuMuX, real-world application

 Ilja Kröker
Moment Matching for Uncertainty Quantification in Process Modelling machine learning, geostatistical modelling, process modelling Stefania Scheurer
Deep-aPC-NN vs. Kolmogorov Arnold networks (KAN) deep learning, PCE Nils Wildt
Sampling with Noisy Gradients MCMC,
sampling		 Tim Brünnette
Deep Learning of Trend Function in Non-Stationary Groundwater Process

machine learning, groundwater modelling

 Waqas Ahmed
Hydrologie, Wasser- und Umweltsystemmodellerierung hydrological modeling,
geostatistics,
precipitation modeling,
CO2 storage modeling, geothermal modeling 		 Jochen Seidel
Learning PFAS isotherms with Universal Differential Equations finite volume method,
mechanism learning, surrogates		 Nils Wildt
Predicting Fracture Path Statistics stochastics,
statistics,
machine learning,
CNNs		 Tim Brünnette

 
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