Student project

No available projects at the moment. Please review ongoing research here.

Comprehensive Proteomics Analysis and Minimal Residual Disease (MRD) Detection in Mantle Cell Lymphoma (MCL) for Treatment Decision-Making and Early Relapse Detection

Embark on a ground-breaking journey at the intersection of cutting-edge proteomics and clinical precision medicine. As a key participant in this project, you'll delve into the dynamic world of MCL, where we are not just deciphering protein expressions but shaping the future of personalized treatment decisions. With a strong emphasis on translating scientific insights into clinical applications and with a robust connection to clinical characteristics, this endeavour holds the promise of changing how we approach, understand, and treat this disease.

Multi-omics analysis of colorectal cancer for improved diagnosis and treatment

We are looking for students interested in improving treatment and diagnostics for cancer through bioinformatic analyses of molecular data.

Development of novel precision cancer therapy based on collateral lethality

We are looking for motivated students that want to develop their skills in laboratory work centered on drug screening in cell and organoid models, or students that want to work with bioinformatic analysis to search for new potential targets to study.

Machine learning for automated analysis of radiology examinations

Machine learning and computer vision is gaining traction in clinical radiology. We are looking for students to participate in model development and building of different automated pipelines for clinical radiology tasks.

Clinical or translational research on adult cancer cases in U-CAN

Opportunity for students to work with clinical data or sample analyses based on the cancer cases included in U-CAN.

Biomarker discovery for detection of cancer

We are looking for students that want to participate in analysis of large-scale omics data to find and validate cancer biomarkers.

Identification of long non-protein-coding RNAs collaborating with PRC2 in MM

Multiple myeloma (MM) despite becoming increasingly treatable remains to date incurable and accounts for the second most common hematological cancer. This warrants innovative approaches into tackling the disease overtly complex genetic background. Our research aims is to identify interacting partners with the Polycomb group proteins by RNA immunoprecipitation coupled with next generation sequencing (RIP-seq, CLIP seq or iCLIP) in MM cell lines and primary MM samples. We also aim to identify the genome-specific binding of lncRNAs of interest by chromatin isolation via RNA precipitation (ChIRP) assays coupled to next generation sequencing and mass spectrometry.

No available projects at the moment. Please review ungoing research here

New approaches for molecular diagnostics

Molecular diagnostics will increasingly impact medical practice. Our group develops, applies, and commercializes advanced molecular tools for diagnostic analyses of nucleic acids and proteins in situ and in solution. We welcome students interested in medical applications of the methods.

Extracellular matrix interactions of importance for brain tumor formation

In our projects we incorporate experience of neural stem cells with glioma biology, leveraging the close relationship between these two fields. We focus on the tumor microenvironment with special emphasis on the extracellular matrix and the neuro-inflammatory responses to brain tumors.

Formation and function of lymphatic vascular network – a drug screen

In this project, you will test a library of chemical compounds on zebrafish embryos. Depending on the length of the project, you will perform the pre-screening for toxicity and chemical screens for a number of these compounds. You will acquire competences in zebrafish handling, chemical screen methodology and confocal microscopy.

Generation of new transgenic tools in zebrafish

Zebrafish is an excellent model for fast and efficient generation of tissue specific transgenic reporters. In our lab we have generated a dataset of candidate gene regulatory elements that drive vascular specific gene expression. In this project you will have the opportunity to generate and test constructs for transgenesis. This will validate if the predicted sequences indeed drive the fluorescent expression in correct tissue.