Rare, genetic diseases affect only a few individuals but the high number of different rare diseases make them in total an important part of health sciences - 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 that do affect the same biological process. Challenges in this research are presented by the genetic background variation and life-style influences, which leads to variety in the 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 answer.

The European Joint Programme on Rare Diseases (EJP-RD) 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 demonstratable training in data analysis.

You will 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.

The successful candidate should have:

●      Demonstrable skills in bioinformatics, data sciences or systems biology;

●      Programming skills (ideally in Java) 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 or metabolism;

●      Communication skills in English - written and spoken;

●      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: 4 years.

Temporary employment for 4 years with evaluation after the first year for further employment.

Your salary would be € 2325 gross per month in the first year up to € 2972 gross per month in the fourth year according to the salary scale for PhD-candidates.

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 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 18,000 students and 4,300 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.

http://www.maastrichtuniversity.nl/

NUTRIM - School of Nutrition and Translational Research in Metabolism / Department of Bioinformatics-BiGCaT

NUTRIM School of Nutrition and Translational Research in Metabolism (https://www.maastrichtuniversity.nl/research/school-nutrition-and-translational-research-metabolism) is an interfaculty research institute of the Faculty of Health, Medicine, and Life Sciences. NUTRIM conducts research in the field of nutrition and metabolism. This research is both fundamental and applied in nature.

NUTRIM offers a PhD training programme for students who aspire a broad understanding of human nutrition, metabolism and toxicology, next to outstanding research capabilities. NUTRIM researchers also teach in several master’s programmes, such as ‘Biomedical Sciences’, ‘Physician Clinical Scientist’ and ‘Health Food Innovation Management’.

The department of Bioinformatics-BiGCaT is part of NUTRIM the school of Nutrition and Translational Research in Metabolism and also affiliated with the Maastricht Institute of Systems Biology (MACSBIO) and MHeNS, the school for Mental Health and Neuroscience. 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 collected , integrated and combined with existing knowledge

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.