Master Projects Available

Please find here below a list with the possible supervisors and projects for a master thesis.

Internal:

Main Supervisor Project

Riccardo De Bin

 Statistical learning for chemistry applications
Riccardo De Bin Gradient boosting for survival analysis
Ingrid Hobæk Haff Fraud detection using copula regression with vine copulas
Ingrid Hobæk Haff Generative models for discrimination
Gudmund Horn Hermansen Conformal prediction for financial time series
Johan Pensar High-dimensional Bayesian estimation of causal effects with directed graphical models
Johan Pensar High-dimensional approximate Bayesian structure learning of undirected graphical models
Johan Pensar Generative probabilistic classification with graphical models
Ida Scheel A Bayesian recommendation system for slate click data
Ida Scheel Conflict analysis for parameters in complex Bayesian models
Morten Stakkeland Leaking cooling system analysis
Geir Olve Storvik Bayesian neural networks
Geir Olve Storvik Sequential Monte Carlo
Erik Vanem Probability distributions of ocean wave crest heights in different sea state conditions

External (an internal co-supervisor will be assigned as well):

Main Supervisor Project
Theophilus Quachie Asenso, Manuela Zucknick Private empirical risk minimization for classification problems with application to health data
Theophilus Quachie Asenso, Manuela Zucknick Modeling interaction effects with multi-omics data
Azzeddine Bakdi Sensor data-based prediction of lithium plating in lithium-ion battery cells
Joseph Sexton, Amirhossein Khazemi, Eirik Klami Kristianslund, Siri Lillegraven Automated coding of adverse events in clinical studies according to the MedDRA classification
Øystein Sørensen R implementation of spatiotemporal models for analysis of MRI data
Øystein Sørensen Use of cyclic continuous variables when analyzing brain measurements
Valeria Vitelli Bayesian Variable Selection for Clustering Genome-wide Transcriptomic Data
Zhi Zhao, Manuela Zucknick Biomarker identification for cancer patients’ survival prognosis using multi-omics network information
Zhi Zhao, Manuela Zucknick Bayesian multivariate mixed models in high-dimensional settings

 

Published Oct. 3, 2022 2:31 PM - Last modified Sep. 2, 2024 11:08 AM
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