Two open Master’s thesis positions
Currently you can apply for two open Master’s thesis positions in the Biochemical Network Analysis group:
Master’s Thesis: Community metabolic modeling of the vaginal microbiome in health and disease
Background
Apply for the Master’s Thesis in the research group Biochemical Network Analysis.
Background
The vaginal microbiome (VMB) is a low-diversity, functionally specialized ecosystem typically dominated by a few Lactobacillus spp. that maintain acidic pH and protect against pathogens. Disruption leads to highly prevalent conditions–bacterial vaginosis (BV; 23–29%) and vulvovaginal candidiasis (VVC; ˜138 M women)– with substantial economic costs, adverse pregnancy outcomes, and cancer progression via chronic inflammation. Despite extensive metagenomic and metabolomic profiling, causality and mechanism remain unresolved due to host DNA contamination, limited capture of metabolic fluxes, and an inability to model competitive interactions or host responses. This project aims to address these issues by using community genome-scalemetabolic models (GEMs) of the vaginal microbiome, combined with vagina-specific host GEMs, to simulate the synthesis and impact of biogenic amines, which are harmful compounds associated with conditions such as bacterial vaginosis.
Aims of the Project
This project includes the following aims:
- Refine reconstructed GEMs from vaginal microbiome using predefined sets of metabolites.
- Reconstruct GEMs for fungi in the microbiome and tissue-specific GEMs of vaginal epithelial cells using transcriptomics data.
- Simulate and analyse community behaviour under health and disease using community GEMs and host-microbe interaction simulation to explore the biosynthesis and impact of biogenic amines.
The duration of this project is set to 9 months.
What we offer
- Great working atmosphere in a young and dynamic group working on computational biology
- Access to state of the art computation environment
- Cosupervision by a PhD student and a Postdoctoral researcher
- Participation in group meetings and discussion about projects within the group or beyond
For applications, please contact juergen.zanghellini@univie.ac.at.
Efficient Chinese hamster ovary (CHO) Cell Factories for Difficult-to-Produce Biotherapeutics
Background
Apply for the Master’s Thesis in the research group Biochemical Network Analysis.
Background
Recombinant proteins are essential for modern therapeutics, yet many remain difficult to produce efficiently in Chinese Hamster Ovary (CHO) cells - the standard industrial host. Even under optimized conditions, production yields vary widely between proteins, and for many targets, productivity remains low and unstable.
Traditional explanations based on gene expression levels or basic protein properties fail to account for this variability. Instead, increasing evidence suggests that specific interactions between the host cell and the recombinant product — such as protein-protein interactions, proteolytic degradation, and microRNA-mediated regulation — play a decisive role in limiting production.
While individual examples have shown that disrupting such interactions can significantly improve yields, these effects are typically identified in a case-by-case manner. A systematic and scalable approach to iden-tify these hidden bottlenecks is currently missing.
Aims of the Project
The aim of this project is to experimentally validate computationally predicted host-product interaction targets to improve recombinant protein production through targeted genetic perturbations in CHO cells.
- Selection of high-confidence host–product interaction targets based on computational analysis.
- Establish CHO-based expression systems by transiently expressing selected recombinant proteins under reproducible baseline conditions.
- Perform targeted genetic perturbations of host factors using shRNA-mediated knockdown to assess their impact on protein production.
- Quantify recombinant protein titers (e.g., ELISA) and calculate specific productivity under control and perturbed conditions.
- Evaluate whether perturbations improve production in agreement with predicted host–product inter-action mechanisms.
The duration of this project is set to 9 months.
What we offer
- A multidisciplinary computational–experimental project in CHO cells.
- Hands-on training in mammalian cell culture, transient transfection, and genetic perturbation.
- Access to state-of-the-art computational and laboratory infrastructure.
- Close supervision by a PhD student and a Postdoctoral researcher.
- Integration into a collaborative research environment within the systems bio(techno)logy.
For applications, please contact juergen.zanghellini@univie.ac.at.
Join us!
We extend an invitation to Postdoctoral, Doctoral, Master's, and Bachelor's students with interest in bio/cheminformatics, network analysis, and computational biology.
- Bio/cheminformatics
- computational mass spectrometry
- high-performance computing
- Network analysis (constraint-based)
- modeling of metabolism
- multi-omics integration
- rational cell factory design
- optimal fermentation design
- Computational biology
- theory of microbial (community) growth
Broaden your expertise, create new knowledge, and excel as a member of our research group. To take the next step, please send your application to juergen.zanghellini@univie.ac.at.