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PhD Student Safe-by-Design Nanomaterials
Maastricht University - Department of Bioinformatics
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 15,000 students and 4,000 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 Humanities and Sciences, Faculty of Arts and Social Sciences, Faculty of Psychology and Neuroscience.
New engineered nanomaterials increasingly find their way to the European market, because of their unique applications. Understanding the (lack of) safety of nanomaterials is therefore of utmost importance. This project is in the context of a EU FP7 project within the NanoSafety Cluster (NSC, www.nanosafetycluster.eu/), and will explore and contribute to the required bioinformatics and statistical solutions in order to develop predictive models of safety-related properties. As such, it can support the development of better and safe-by-design nanomaterials. Within the project you will develop solutions based on ontologies, cheminformatics, and chemometrics to support and guide Safe-by-design engineering of new materials by international partners in the NSC community. The outcome of your research will be novel nanoQSAR methods using state-of-the-art data exchange technologies that help explain the biological and chemical mechanisms and pathways involved in the safety of the various types of nanomaterials.
We seek a candidate with strong academic abilities and the ambition to become an excellent researcher. You have completed a research master (MA, MSc, MPhil) in the natural sciences, or an equivalent 2-year degree. Outstanding students with a 1-year regular master can be accepted in exceptional cases when their profile exactly matches the requirements for this research project. We are looking for a prospective PhD candidate with (in random order):
A background in material science, toxicology, or nanotechnology, but also with affinity for data integration issues (e.g. ontologies) and quantitative methods (e.g. regression methods);
Strong analytical capacity;
Good organisational skills;
Affinity working in an interdisciplinary and highly international environment;
Excellent writing skills in English;
Willingness and proven ability to work in a team;
Working knowledge of source code development (version control, issue trackers, documentation);
A track record in scientific software development;
Proficient knowledge of multivariate statistics;
Familiarity with the use and limitations of Open Science approaches;
Willingness to relocate to (the vicinity of) Maastricht.