The newly formed Systems Medicine lab at the Centre for Host-Microbiome Interactions develops Genome-scale metabolic models (GEMs) as well as Integrated biological networks (INs) for human cells/tissues to study the interactions between the host tissues and microbiome. These comprehensive models are also employed in the analysis of the omics data obtained from subjects with complex diseases including obesity, Non-alcoholic fatty liver disease (NAFLD) (Mardinoglu et al, Molecular Systems Biology, 2017, Mardinoglu et al, Cell Metabolism 2018), Type 2 diabetes (T2D) (Lee et al, Cell Metabolism 2016) and certain types of cancer (Uhlen et al, Science 2017). This is an exciting area of biomedical research, driven by the rise of common metabolic disorders as well as recent discoveries of metabolic reprogramming in cancer.
We are seeking a PhD candidate with strong computational skills to generate GEMs and INs for human:
1. Brain (Reference number: 2019/DOCS/01)
2. Heart (Reference number: 2019/DOCS/02)
3. Kidney (Reference number: 2019/DOCS/03)
The candidates will use these biological networks in the analysis of the omics data obtained from different clinical conditions:
1. Alzheimer and Parkinson diseases
2. Cardiovascular diseases
3. Kidney diseases
- to identify drug targets and discover biomarker for the development of the efficient treatment strategies accounting the effect of host-microbiome interactions. The candidates will be working closely in collaboration with the experimental groups, clinicians as well as number of big pharma companies.
The candidate with excellent written and oral communication skills is expected to perform research in Systems Biology, Systems Medicine, Network Medicine and Bioinformatics. We seek highly motivated individuals with a Master of degree in Computational Biology/Bioinformatics or equivalent master degree in Engineering related to Computer Science or. In the latter case, candidates should have interest in bioinformatics, especially topics related to biological networks and different omics technologies.
The candidate should be highly motivated for doing scientific research related to human diseases and should have well developed analytical and problem-solving skills. The candidate should also have a strong background in applied mathematics or bioinformatics. The candidate should also be adept at programming numerical algorithms in languages such as MatLab, R and Python.
Students will be trained in Systems biology. Systems biology is an interdisciplinary subject where the systems of biological components are studied using mathematical models, computational models and experimental technologies such as genomics, proteomics, transcriptomics and metabolomics. It includes application and development of systems biological methods with particular emphasis on integration, analysis and modelling of big data within the field of molecular biosciences.
To view entry requirements, application information and further details, please visit: http://bit.ly/2019-DOCS-01-03