The research group of Prof. Bob van de Water aims to unravel cell signaling programs that underlie adverse xenobiotic-induced adverse responses as well as anticancer drug resistance. In particular, high throughput transcriptomics analysis is applied with innovative co-regulated gene network analysis thus contributing to a system toxicology approach in qualifying and quantifying adverse responses.
We are seeking a candidate with a strong interest in bringing toxicogenomics to the next level by improving its interpretation and dose-response analysis and FAIRification.
In this project the candidate will work on innovative (data) approaches within PARC
(Partnership for the Assessment of Risks from Chemicals), actively participating in further implementation of the co-regulated gene networks framework for chemical hazard assessment. In particular, the candidate will design approaches to improve interpretation of gene co-expression modules, including defining ontologies (connecting to the AOP framework) and implementing benchmark dose analysis for gene network analysis.
In addition, the candidate will be (jointly) responsible for the implementation of PARC FAIR Research Data Management (RDM) policies developed through the PARC project. This includes alignment of the above-described research with FAIR principles, and FAIRification of the OMICS workflow. You will also advise researchers involved in the PARC project on compliance with the FAIR data and Open Science principles in all stages of the research cycle: collection, storage, archiving, and reuse of data. You will provide support in the writing of Research Data Management Plans for the PARC researchers, as well as training, workshops, communication, guidelines, and checklists. You will also contribute to developing an excellent data infrastructure (local, national and international).
The prospective candidate will join an enthusiastic research team of >25 researchers that conduct their work in the context of multiple past and current European-funded projects (EU-ToxRisk, RISK-HUNT3R, eTRANSAFE, TransQST, VHP4Safety, PARC, DISCERN) and grants funded by the EFSA (TD-TRAQ, TXG-MAP), where successful interactions between academia, industry, and regulatory agencies assure excellent scientific and societal impact, as well as a strong support network.
The successful applicant will:
- Contribute to scientific advancements of co-expression methods in the toxicology context, in particular in combination with bench-mark dose analysis;
- Development of interpretation ontology for co-expression methods in the toxicology context, in particular in combination with the AOP framework;
- Contribute to the further developments of the co-expression application TXG-MAPr tool (https://txg-mapr.eu/, R-Shiny);
- Design and apply case studies to demonstrate the value of co-expression methods and the TXG-MAPr tool for risk assessment;
- Implement data management policies and guidelines from the PARC consortium;
- Monitor data management implementation of those policies within work packages (WP5 and WP6) in which Leiden University is involved;
- Develop guidelines and provide training in data management according to the FAIR principles to researchers;
- Be and stay informed about local but also (inter)national developments in the field of FAIR data management;
- Interface with multiple partners in collaborative projects.