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The research position is part of the European FNS (Food Nutrition Security)-Cloud project. FNS-Cloud (http://www.fns-cloud.eu/) will overcome fragmentation problems by integrating existing FNS data, which is essential for high-end, pan-European FNS research, addressing FNS, diet, health, and consumer behaviors as well as on sustainable agriculture and the bio-economy. Current fragmented FNS resources not only result in knowledge gaps that inhibit public health and agricultural policy development, and the food industry from developing effective solutions, making production sustainable and consumption healthier.
As a larger context for the work linked to this vacancy, FNS-Cloud will provide data and analytical tools to allow three demonstrators; agri-food, nutrition & lifestyle, and noncommunicable diseases & the microbiome. This should facilitate:
(1) Analyses of regional and country-specific differences in diet including nutrition, (epi)genetics, microbiota, consumer behaviours, culture, and lifestyle and their effects on health (obesity, noncommunicable diseases (like diabetes), including the roles of ethnicity and traditional foods), which are essential for public health, and agri-food and health policies;
(2) Improved understanding of agricultural differences within Europe and what these mean in terms of creating sustainable, resilient food systems for healthy diets; and
(3) Clear definitions of boundaries and how these affect the compositions of foods and consumer choices and, ultimately, personal and public health in the future.
You will be involved in building the infrastructure for the FNS-Cloud. This will include the development and application of advanced methodologies for data preparation, analysis, and visualization. The following tasks are essential for building the FNS-Cloud infrastructure:
● Pre-processing of Food and Nutrition data (quality control, data pre-processing using existing (but possibly amended) workflows, normalization, and basic statistics
● Curation and annotation of Food and Nutrition data (included both capturing of study descriptions and data preparation needed for analysis and integration)
● Integration of Food and nutrition data, including (FAIR data capture) tool and ontology development
● Analysis and visualization of Food and Nutrition data (mostly based on existing tools like PathVisio and Cytoscape, possibly with new plugin development)
● Implementation of secure food and nutrition services (making services available in the cloud, integration in workflows and providing software containers).
In addition, the researcher will be part of the demonstrator study within FNS-Cloud on noncommunicable diseases & the microbiome. This will include developing an analysis pipeline for the integration of metagenomics and metabolomics data and their integration.
We invite applications from candidates who meet the following requirements:
● A PhD in Bioinformatics or Systems biology or Computer Science (or a closely related field)
● Excellent programming skills or the willingness to acquire them, ideally already applied in a collaborative development environment
● Experience in building data analysis infrastructures
● Preferably experience in ontology development and data integration
● An interest in noncommunicable diseases and the microbiome
● Affinity for working in an interdisciplinary and highly international environment
● Willingness to relocate to (the vicinity of) Maastricht
● An outstanding research and publication record
● Fluent command of English, both oral and in writing
● Proven organisational skills and professional behaviour
Fixed-term contract: 36 maanden.
We offer a three years, 1.0 fte appointment as a junior researcher or post-doctoral researcher starting beginning of 2020. The employment period will be for one year with the perspective of prolongation after evaluation.
Remuneration will be according to Collective Labour Agreement of the Dutch Universities in scale 10 with a minimum of € 2.709 and a maximum of € 4.274 gross per month (depending on your experience) for a full-time position of 38 hours/week. On top of this, there is an annual holiday allowance (8% of annual income) and an annual end-of-year bonus (8.3% of annual income).
Applicants from outside the Netherlands may be eligible for the so-called 30% ruling, a tax cut for highly skilled migrants that applies for a maximum of five years. If you are moving to Maastricht from more than 40 kilometers away, you may qualify for a one-time reimbursement of your relocation costs.
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.
The department of Bioinformatics-BiGCaT is part of NUTRIM the school of Nutrition and Translational Research in Metabolism. 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.