PhD position "Multi-Omics Network Reconstruction during plant development

Are you an aspiring researcher looking for an interdisciplinary and fundamental PhD project in the field of statistics, mathematics and machine learning? Would you like to contribute to our research on developing statistical methodologies and tools to model multi-omics data, and are you interested inplant development in response to the environment?Then we are looking for you!

The plant cell is a complex system of interacting molecules. Most biological characteristics (e.g. plant development) arise from complex interactions between the cell's numerous components. Therefore, inferring networks and dynamics of genes, proteins, metabolites and other biological entities from high-throughput biological omics data is a central and challenging issue in computational and systems biology. In this project, you will develop statistical modeling tools for identifying complex high-dimensional associations. The aim is, to develop state-of-the-art methods that will enable you to reveal previously unnoticed patterns in both existing and new datasets. These methods will allow you to pinpoint novel molecular mechanisms and elite genes that influence the interaction between different omic levels during plant development, and thus a priority list of genes to be tested experimentally.

Experimentally, the project focusses on nodule initiation during the legume-rhizobium symbiosis. In this symbiosis, formation of specialized root organs (nodules) is initiated upon perception of bacterial secreted signaling molecules. These so-called Nod-factors trigger cell divisions in specific region of the root, giving rise to the nodule. During this initiation, massive changes occur in the expression level genes, proteins and metabolites. However, how these dynamics contribute to the activation of the cell cycle in specific root cells remains unknown. In part, this is due to a lack of high-resolution data, but also the absence of appropriate statistical tools to deal with complex multi-omics datasets. Tools you will co-develop during the course of this PhD research.

The project is embedded within the chairs ofApplied Statistics andtheLaboratory of Molecular Biology of Wageningen University and Research (WUR). You will focusoncreating a new theoretical framework for modeling mechanistic relationships between, for example, transcriptomics and metabolomics from multi-omics data. The project offers rich and challenging research opportunities on the interfaceofstatistics andmolecular biology.Our ideal candidate would be someone with strong skills in statistics and an interest in experimental plant science.

In this multi-disciplinary setting, you will be supervised by Dr. Pariya Behrouzi (Applied Mathematics and Statistics) and Dr. Wouter Kohlen (Laboratory of Molecular Biology). In addition, you will be co-supervised by Prof. Fred van Eeuwijk and Prof. Ben Scheres.