Masterarbeiten

Kontakt: Manfred.Claassen (at) med.uni-tuebingen.de

Kontakt: tjeerd.dijkstra (at) uni-tuebingen.de

Lab Name: Health NLP Lab
Webseite: https://health-nlp.org

Kontakt: carsten.eickhoff (at) uni-tuebingen.de

Forschungsstichpunkte:

• Natural Language Processing
• Explainable AI
• AI Safety
• Clinical AI

Abschlussarbeiten in 2025:

• Agentic Document Textualization with Small Vision-Language Models: An Agentic Pipeline for Scientific Visual Content
• Information Extraction from Breast Cancer Reports for Tumor Boards
• Iterative Retrieval Augmented Generation for Multi-Hop Question Answering
• Using Machine Learning to predict adverse events in patients over 65 years undergoing cardiac surgery
• Christmas is coming bald: Exploring Representations of True Cognates and False Friends in Multilingual LLMs
• Machine learning based investigation of physical activity in mid-life parents: A multi-factorial approach
• Privacy in Medical AI: Evaluating Risks and Countermeasures for Protecting Patient Information
• Information Extraction from Radiation Oncology Reports
• From Geometry to Performance - Analyzing Embedding Space Structure in Large Language Models
• Understanding Unreliability of Steering Vectors in Language Models
• TruthAlign: Enhancing Fact-Checking Using Conflicting Words
• SPOT: Sparse Parameter-efficient Outlier-guided Tuning
• Contrastive Attribution Learning in Explainable Neural Text Classification
• Developing an Intelligent Search Engine for Cancer Therapy and Medication Documents Using Lucene and Advanced Relevance Algorithms

Kontakt: daniel.huson (at) uni-tuebingen.de

Forschungsstichpunkte:

• Phylogenetics
• Metagenomics
• Algorithms
• Software

Masterarbeiten in 2025:

• Enhanced sketch-based taxonomic assignment of metagenomic data genomes
• Genomics-to-Function: rBOX, Synteny, and Genome-Resolved Taxonomy of a Chain-Elongating Bioreactor Isolate
• Design and Implementation of a Memory-Efficient, Multithreaded Taxonomic Classifier for Long Reads using Double Indexing
• Chromosomal rearrangements and structural variation underlying speciation in brown algae
• The abundance of neurotransmitter-producing microbiota, bacteriocin gene clusters, and antibiotic-resistant genes in diabetic foot ulcers

Kontakt: oliver.kohlbacher (at) uni-tuebingen.de

Forschungsstichpunkte:

• Translational bioinformatics
• Computational mass spectrometry
• Personalized medicine
• Research data infrastructures

Masterarbeiten in 2025:

• CLAUDIO 2.0: A web application for efficient automated structural analysis of cross-linking data
• Investigating Sequence Co-evolution of the Human Mitochondrial Interactome
• Integration of a Halogen Specific Neural Network into GNINA
• Comparison of Quantum Mechanical Methods for Determining the Vmax of Halogenated Compounds

Our group would be fine with either bachelor's or master's theses, as long as the students write their thesis in English.
We offer thesis topics on infection biology, computational drug discovery and method development for molecular dynamics and simulations. We are happy to discuss specifics over coffee and would appreciate it if the students sent a short motivation letter and CV.

Contact: thales.kronenberger (at) uni-tuebingen.de

Unsere Forschungsthemen:

• AI for Medical Imaging (MRI, CT, PET)
• Multimodal Data Integration (Imaging + Clinical Data)
• Clinical Applications & Large-Scale Cohort Studies (NAKO, UK Biobank) 

Informationen über aktuelle Themen finden Sie hier: https://www.medizin.uni-tuebingen.de/de/das-klinikum/einrichtungen/kliniken/radiologie/allgemeine-radiologie/forschung/ag-midas/teaching

Bitte senden Sie Ihre Bewerbung mit Angabe Ihres gewünschten Fachgebiets / Ihrer gewünschten Fachgebiete, Lebenslauf und Transkript an: midaslabthesis (at) gmail.com

Masterarbeiten in 2025:

• Multimodal biological age estimation: Disentangling redundancy, uniqueness, and synergy of multimodal information
• Deep Learning-based prediction of representative MR-Guided breast biopsy
• Learning feature matching with foundation model guidance for motion correction in quantitative MRI
• Improving Diagnosis of Alzheimer's Disease with Interpretable Models
• Evaluating Interactive Deep Learning Approaches in Brain MRI Segmentation
• Contrast-Invariant Motion Correction Network for multi-parametric MRI
• Analysis for sustainable MR imaging operation
• Multimodal contrastive learning for biological age regression
• Unsupervised Keypoint-Based Registration for Parametric MR

Forschungsarbeiten in 2025:

• Multimodal Biological Age Estimation at Different Timepoints
• Deep learning-based MR Guided Breast Biopsy
• Landmark Detection in Interventional Magnetic Resonance Imaging During Breast Cancer Biopsy
• Medical Dashboard for epidemiological studies
• Medical Data Analysis and Visualization in the UK Biobank and NAKO
• Image quality assessment
• Machine learning-based analysis on the energy efficiency of magnetic resonance imaging

Forschungsstichpunkte:

• Protein sequence and structure analyses
• Machine learning approaches to protein structure prediction and design
• Prediction and classification of protein-protein interactions

Kontakt: andrei.lupas (at) tuebingen.mpg.de

Bitte fügen Sie bei Ihrer Anfrage nach einem Thema für Ihre Abschlussarbeit Ihren Lebenslauf, Transkripte und eine Liste der Methoden bei, die Sie ohne intensive Betreuung durchführen können.

Masterarbeiten in 2025:

• Investigating Sequence Co-evolution of the Human Mitochondrial Interactome
• CLAUDIO 2.0: A web application for efficient automated structural analysis of cross-linking data

Kontakt: sven.nahnsen (at) uni-tuebingen.de

Link: https://uni-tuebingen.de/de/140699

Forschungsstichpunkte:

• Analysis and visualization of genomics
• Transcriptomics and/or proteomics data
• Analysis of (ancient) (pan-)genomic data, of expression data and of the transcriptome's architecture of prokaryotes
• Development of machine learning methods for dimensionality reduction and for analysis of proteomics data.

Vergangene Masterarbeiten

Kontakt: Dr. Thorsten Schmidt

Kontakt: nico.pfeifer (at) uni-tuebingen.de

Kontakt: timo.sachsenberg (at) uni-tuebingen.de

Forschungsstichpunkte:

• Genome graphs
• Pangenomes
• Hyperdiverse regions of the genome

Abschlussarbeiten in 2025:

• Genomic diversity of a local blast fungus population in Italy
• Genomic hypervariability of the essential gene P5CR in Arabidopsis thaliana
• Identification of novel gene duplication events in Arabidopsis thaliana genomes

Bewerbung ist lt. Webseite des Max-Planck-Instituts direkt an die betreffende Projektleiterin / den betreffenden Projektleiter zu senden.

Kontakt: nadine.ziemert (at) uni-tuebingen.de