PhD positions in experimental and computational sciences for the
Marie-Curie Innovative Training Network “PoLiMeR”
Metabolic diseases are a burden on the European population and health care system. It is increasingly recognised that individual differences with respect to history, lifestyle, and genetic make-up affect disease progression and treatment response. A Systems Medicine approach, based on computational models fed with individual patient data, has the potential to provide the basis for a personalised diagnosis and treatment strategy. The PoLiMeR consortium (Polymers in the Liver: Metabolism and Regulation) has identified the inherited, liver-related diseases of glycogen and lipid metabolism as the ideal starting point for innovative research training in personalised ‘Systems Medicine’. These diseases are life-threatening for children. Since each specific disease is rare, research efforts are diluted. Our system-based perspective opens possibilities for the application of novel drugs and diagnostic tools to a range of different diseases.
To advance diagnostics and treatment of metabolic diseases beyond the state-of-the-art, a new generation of scientists is needed. The complexity of the metabolic network and its aberrant behaviour in disease require truly interdisciplinary researchers, trained in the three ‘pillars of Systems Medicine’: experimental, computational and clinical research. PoLiMeR aims to train you as a talented PhD student in this field. We bring together clinical, academic, and industrial experts on inherited metabolic diseases, computational modelling of the entire human metabolism, organ-on-chip technology, and detailed metabolic profiling, located in Germany, Luxembourg, Sweden, Norway, and the United Kingdom.
As a PhD student in this project you will be part of a highly international team of young researchers. You will have your individual research project at your host organisation, focusing on your discipline of interest. To complement your specialized training, you will do internships at a complementary PoLiMeR partner organization. In addition, you will follow advanced interdisciplinary courses by leaders in the field of Systems Medicine. Thus, you will be trained to become a Systems-Medicine expert, with expertise in computational and wet-lab techniques, who can collaborate between clinical, academic, and industrial environments.
Are you interested? Please, check the 5 PhD positions that are still open in the PoLiMeR project!
Combinatorial explosion of molecular species
Classically, enzymes are thought to have a specific affinity for one well-defined substrate. In contrast, enzymes acting on larger molecules catalyse the conversion of a functional group in the substrate with a lesser specificity for the remaining part of the molecule. This promiscuity results in a combinatorial explosion of different molecular species, particularly in lipid metabolism. The challenge is to develop innovative analytical methods and genome-scale modelling approaches to analyse and interpret complex lipid profiles in a meaningful way, and apply these to clinical samples and data to identify novel causes of patient-to-patient variability.
PhD student 1: Stoichiometric modularisation of combinatorial lipid metabolism
Host organisation: National University of Ireland, Galway, IT
The PhD student will develop a novel approach to represent promiscuous enzymes (enzymes acting on lipid classes rather than on single lipid species) more efficiently in a genome-scale model (GEM). This innovation will be implemented in a comprehensive genome-scale model of human metabolism. The problem of combinatorial explosion of possible lipid molecular species in current computational models will be addressed by dividing the existing reactions for synthesis of complex lipids into a set of modular synthesis and degradation reactions, based on the concept of conserved moieties, resulting in a stoichiometric matrix that admits integral flows (integer reaction rates). Each integral flow shall represent the synthesis and degradation of a different combination of lipid molecular species. The PhD student will map lipidomics data in the metabolic network analyse computationally different disease specific scenarios.
If enzymes catalyse multiple reactions, alternative substrates compete with each other for binding to the enzyme, thereby inhibiting each other’s conversion. This implies that only a fraction of the total enzyme capacity is used for a specific reaction. At the level of metabolic pathways and networks this causes feedback and feedforward inhibition and may lead to complex dynamics, which has hitherto hardly been explored. The challenge will be to develop novel experimental tools and computational models to analyse the impact of substrate competition on pathway dynamics, and apply these to patient samples and data to identify putative therapeutic targets
Data and model management
A key challenge in Systems Medicine research is making the extremely diverse data FAIR. FAIR means Findability, Accessibility, Interoperability and Reusability of data. Within this project we base ourselves on the FAIRDOMHub, a platform for FAIR data, and explore improving the Findability of data using information retrieval methods. How can we enable users to store their results in a way that the results are most easily found, even if the query is imprecise?
PhD student 2: Data and model management and information retrieval
Host organisation: HITS gGmbH, Heidelberg DE
You will be employed and do the research at HITS. In addition you will be registered at the University Medical Center Groningen (NL) to obtain the PhD degree.
The PhD student will provide FAIR data management services to the PoLiMeR consortium based on the FAIRDOM Hub (the data sharing site hosted at HITS) and on GitLab. The PhD student will use the database generated in the PoLiMeR project together with pre-existing and public data in the to determine how changes in data collection, metadata quality and data feature extraction affect the information that can be found. The PhD student will seek to improve existing tools for data collection as well as querying at critical points.
We are looking for graduates in computer science who are aiming for a Doctorate. This topic is particularly interesting in that it provides quite general challenges (How to I tailor information retrieval and information storage algorithms such that they work best in combination?); at the same time, there are *real* users to cater to. These users can help in finding out the best combination of data enrichment/search algorithm in real life, in an exciting application area: The life sciences.
Eligible candidates for a PhD position in the PoLiMeR training network should have the following qualifications:
- A(n) (almost) completed master degree in a discipline relevant to the PhD position(s) for which you apply.
- Strong motivation for scientific research in an interdisciplinary and international environment
- Excellent English presentation and writing skills
- Good organisational and communication skills, being a team-player
Successful candidates must fulfil the criteria defined by the European Commission:
- As an Early Stage Researcher, you have to be in the first four years of your research career and have not been awarded a doctoral degree at the time of recruitment.
- At the time of recruitment by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host organisation for more than 12 months in the 3 years immediately prior to the reference date.
The start of the PhD projects is envisaged between April 2019 and September 2019.
Application and contact
You are invited to apply if you are interested in one of the PhD positions. Please send your CV and motivation letter to firstname.lastname@example.org. Please indicate in your motivation for which PhD position(s) you are applying.
For more information about a specific position please contact the person indicated for that position.