Bacteriology

Galardini Lab

Marco Galardini
Head

Prof. Dr. Marco Galardini

Research focus

The advent of molecular biology has propelled biology at the forefront of modern science. Technological advances such as rapid and inexpensive DNA sequencing are paving the way for precision medicine and synthetic biology to become ubiquitous in clinical and industrial applications. Basic research is needed to spearhead the development of these technologies into everyday practice. Microbiology is one of the areas that could benefit the most from this technological acceleration. For instance, the rise of antimicrobial resistance (AMR) requires the development of new approaches aimed at predicting evolution of resistance and prevent it. Sequencing-based surveillance and evolutionary models informing smarter treatment strategies are therefore urgently needed. At the same time, the recognition of the role of the microbiome on human health and as a possible treatment strategy for infections requires a deeper ecological and functional understanding. In particular, the design of treatments is predicated on knowing the molecular and metabolic functions encoded in the genomes of each member of the microbiome. In short, we need to greatly improve the functional and evolutionary interpretation of genomic sequences, at the same time as they are being produced. These challenges can be effectively tackled using a data-intensive approach, favored by high-throughput molecular techniques and computational biology.

Funding

  • RESIST
  • DFG (GA 3191/1-1 / HA 3299/8-1) “Einfluss der COVID-19 Pandemie Hygiene- und Abstandsregeln auf die Übertragung Gram-negativer multiresistenter Erreger in Krankenhäusern”

Prof. Dr. Marco Galardini is a member of the RESIST cluster of excellence

In the following video he explains his research focus in RESIST. Further information about Marco Galardini in RESIST can be found here.

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Jobs

PhD Student Position in Computational Biology

We are looking for a candidate to fill a computational PhD student position, with the main task of better understanding which genetic elements (“genes”) make bacterial pathogens such as E. coli, K. pneumoniae, P. aeruginosa, and E. faecium virulent and resistant to antibiotics. We have in fact developed methods (here and here) to sift through large numbers of bacterial genomes for this exact purpose (see here, here, and here), and it will be the job of the candidate to use and improve these methods so that they can be applied to an even larger number of genomes. We are also particularly interested in implementing more machine learning methods and to integrate molecular phenotypes such as gene expression and proteomics.Our lab is part of the RESIST excellence cluster at Hannover Medical School (MHH), and we are part of a collaborative project with Susanne Häussler and Meike Stiesch to identify genetic determinants of pathogenicity and virulence in life-threatening bacterial infections.We are looking for a candidate with a strong computational background and relevant technical skills:Strong background in computational biology, bioinformatics, computer science, or a related field.Experience with programming languages such as Python and workflow management systems such as Snakemake.Familiarity with machine learning techniques and libraries (e.g., scikit-learn, TensorFlow, PyTorch).Knowledge of bacterial genomics and related bioinformatic tools.Experience with high-performance computing (HPC).Experience with version control systems (e.g., git) and software development best practices.Experience with statistical analysis and data visualization.We offer a fully-funded PhD position for a little longer than 3 years, to begin in February 2026. The student will be enrolled in the Biomedas graduate program, which offers curriculum specifically designed for computational biology students. The lab is located at Twincore, embedded in a large scientific campus that include Hannover Medical School, and the Center for Individualized Infection Medicine (CiiM); we are also part of the Helmholtz Centre for Infection Research (HZI), which offers lots of opportunities for collaboration.