Rare, genetic diseases each affect only a few individuals but the high number of different rare diseases means that about 1 of 17 people is affected by a rare disease. Rare diseases are often caused by genetic variants especially loss of function mutations. We can study the effects of such mutations on human phenotype - health and disease.  The approach we use benefits from the fact that different patients often have different mutations sometimes even in different genes that do affect the same biological process. Challenges in this research are presented by the genetic background variation and life-style influences. This leads to variety in disease presentation and problems in the identification of suitable drugs. Integrative systems biology, using pathway and network analysis approaches, is one of the ways to integrate experimental data and information from different resources in order to get a comprehensive insight. This can then be used to identify disease processes, important lifestyle factors like from nutrition and to find new drugs or new drug applications.   

The European Joint Programme on Rare Diseases (EJP-RD) is a large pan-European project where many research teams, data scientists and clinicians collaborate. It puts emphasis on studying pathway and network approaches for rare diseases and has identified the integration of genetic variants and environmental data as one of the main challenges. Chris Evelo and Friederike Ehrhart in the Department of Bioinformatics of Maastricht University are leading this work.

Within this collaborative project, we are looking for a PhD candidate with a background in bioinformatics, data sciences, systems biology or life sciences in general with a demonstrable training in data analysis.

You will work in pathway and network biology, evaluate how new integrative systems biology approaches, for which in part new tools will be developed, lead to better understanding, improved diagnosis and treatment of rare disease patients, and this will serve as the basis for your PhD thesis.

Main Tasks and responsibilities

• Contribute to integrative systems biology research in rare diseases leading to a PhD thesis.
• Investigate and develop algorithms and software tools to link genetic variant information, and combine that with for instance information from toxicology and nutritional science from external databases and experimental data and use that for biological pathway and extension, overlap and analysis approaches. For molecular biological networks. Documentation and publication of the results.
   

The successful candidate should have:

• Demonstrable skills in bioinformatics, data sciences or systems biology;
• Programming skills including experience with project management for software projects  (version control, issue trackers, documentation, integrated testing);
• Training in biological sciences, especially molecular biology and genetics ideally with applications in neuroscience and/or metabolism;
• Previous experience with (biological) network analysis or graph data analysis is a pre;
• Good communication skills in English - written and spoken;
• Social and organisational skills needed to collaborate in research and development teams;
• Affinity for working in an interdisciplinary and highly international environment;
• Organisational skills and professional behaviour;
• Readiness to relocate to (the vicinity of) Maastricht.

It is unlikely that you will have covered all aspects, candidates with experience in some of these aspects and an interest in the others are also encouraged to apply.

Fixed-term contract: 48 months.

Temporary employment for 4 years. The first year will be a probation period, after a positive assessment the position will be extended for another 3 years, which happens in the vast majority of cases.

Your salary would be € 2.395,- gross per month in the first year up to € 3.061,- gross per month in the fourth year according to the PhD-candidate salary scale. An 8% holiday and an 8.3% year-end allowance is also provided. Each year an evaluation will take place.

The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website http://www.maastrichtuniversity.nl > Support > UM employees.

Maastricht University

Maastricht University is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. Maastricht University has around 20,000 students and 4,700 employees. Reflecting the university's strong international profile, a fair amount of both students and staff are from abroad. The university hosts 6 faculties: Faculty of Health, Medicine and Life Sciences, Faculty of Law, School of Business and Economics, Faculty of Science and Engineering, Faculty of Arts and Social Sciences, Faculty of Psychology and Neuroscience.
For more information, visit www.maastrichtuniversity.nl.

The Department of Bioinformatics-BiGCaT is part of NUTRIM School of Nutrition and Translational Research in Metabolism at the Faculty of Health, Medicine and Life Sciences. It was founded in 2001 by Prof. dr. Chris Evelo aiming at employing bioinformatics approaches in systems biology to integrate experimental data and data with current knowledge. Integrative Systems Biology is being developed and applied in various research fields. The department has four core research areas; 1) metabolic diseases, 2) micronutrients, 3) toxicity and risk assessment and 4) rare diseases. Within these areas, different types of data, like transcriptomics, proteomics, metabolomics and (epi)genomics data, are integrated and combined with existing knowledge.

Chris Evelo’s BiGCaT group is involved in (inter)national initiatives to collect, share and integrate biological data. Moreover, in order to perform data analysis in a state-of-the-art manner, novel methods and tools are being developed. These include i) high-throughput data analysis pipelines, ii) semantic Web tools using RDF, ontologies and SPARQL, iii) cheminformatics software, iv) structuring and collecting biological processes in WikiPathways, v) pathway analysis in PathVisio and vi) network analysis in Cytoscape.