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The Dutch Wetenschapsagenda project Virtual Human Platform for Safety (VHP4Safety) has a vision to use innovative approaches to determine the safety of chemicals and pharmaceuticals based on human data instead of data from laboratory animals. Within this project, one research line will focus on integrating and analysing high quality data of human biology. Central to this will be systems biology combined with Adverse Outcome Pathways (AOPs) to define and model the underlying mechanisms. This includes quantitative AOPs (qAOPs) to capture the toxicodynamics and distributions of toxicants within the human body, and relate this to data from new model systems. The ultimate outcome is modelled estimates of compound safety.
Within this research line, this position focuses on the ICT infrastructure and will translate experiences with Docker and OpenShift/Kubernetes ideas from the past project OpenRiskNet to this project. Throughout the project FAIR research output is essential for interoperability, which does not only apply to data, but to the application programming interfaces (OpenAPI) too, and knowledge bases such as those developed in the BiGCaT research group (WikiPathways, AOP-Wiki RDF). Around this core you will (co-)develop analysis workflows, e.g. with Jupyter or RMarkdown, to integrate data and knowledge with services and computational resources. A considerable task will be to make services from other work packages available via this platform. Collaboration within the other research projects and with efforts like ELIXIR are a key aspect of this position.
We are looking for a prospective postdoc candidate with either a background in bioinformatics, cheminformatics, ontology development, software development, data science, or equivalent, with affinity for data and service integration issues and systems biology approaches. The ideal candidate will have covered all aspects, but candidates with experience in one of these and an interest in the other are also encouraged to apply.
Fixed-term contract: 12 months, with the possibility of renewal for up to three more years.
We offer a full-time, one-year term position, with the possibility of renewal for up to three more years depending on the performance. Yearly evaluations will take place. Salary range from € 2.790,- to € 4.402,- gross per month (pay scale 10 in accordance with the Collective Labour Agreement for Dutch Universities).
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 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.
Maastricht University (UM)
Universiteitssingel 60, 6229 ER, Maastricht
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