PhD in Computational Biology
PhD in Computational Biology
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Job Description
We are currently looking for a talented PhD student in the context of the FWOSBO funded project MATCHMAKING: Unveiling Optimal SoybeanRhizobia Matches in Northwestern European Environments (4year position). This PhD position is a shared position between the VIBUGent Center for Plant Systems Biology and ILVO.
The VIBUGent Center for Plant Systems Biology (PSB ) is a worldleading plant science institute with the mission to integrate genetics genomics and computational biology to unravel the biology of plants and to improve the sustainability and climate resilience of crops. The Maere lab at PSB () is active in the fields of computational biology systems biology and evolutionary genomics. Current research topics include testing a novel experimental setup (singleplant omics) to unravel the molecular wiring of plant phenotypes under field conditions studying dosage balancesensitive genes in plants and investigating factors affecting soybean yield and rhizobial inoculant performance in the field.
The institute for Agriculture Fisheries and Food Research (ILVO) is a multidisciplinary research institute of the Flemish government with focus on research and innovation in sustainable agriculture horticulture fisheries and food business. Positive proactive professional working together and being an example are the 5 values that guide ILVO employees in the way they approach their work. At the Plant sciences unit we perform research in the field of genetics and breeding agronomy of (new) crops circularity and the efficient use of resources. We also try to understand the processes in the soil. These are key ways to optimize the eco and environmental system around the plant and thus reduce the environmental impact of agriculture. Sustainable cultivation systems and techniques that promote agrobiodiversity are tested and promoted. Wellequipped research greenhouses laboratory and trial field infrastructure with extensive machinery a unique composting site and several rainout shelters for drought research are key assets.
Project description
Soybean is not only a major source of protein for food and feed worldwide but also by interaction with nitrogen (N)fixing rhizobia in the root nodules a sustainable alternative for N fertilizers. The growing global demand for plantbased protein coupled with the need to reduce reliance on imports from deforestationprone areas drives expansion of soybean cultivation into higher latitudes. Indeed to meet European demands for sustainable soybean products production must extend to northwestern regions of the continent. However existing soybean varieties and commercial rhizobia inoculants are not adapted to these environmental conditions resulting in insufficient nodulation and consequently inconsistent highprotein bean yields.
Our goal is to identify soybeanrhizobia matches that are suitable for Northwestern Europe building on a set of endemic rhizobia identified in a previous project. We will achieve this through infield screening and detailed assessment of the performance of a large set of soybeanrhizobia combinations under adverse environmental conditions. Our research will uncover the genomic regions governing efficient nodulation through GWAS analysis in soybeans and explore the potential of native plant growthpromoting rhizobacteria (PGPR) as helper strains. Additionally we will conduct comprehensive analyses of efficient interactions using (meta)transcriptomics in nodules. Our project will pave the way for sustainable highprotein soybean production in Northwestern Europe with the potential to benefit highlatitude regions worldwide.
You will be involved in the setup and execution of the field trials and the analysis of the resulting data (e.g. GWAS linear mixed models) and in the construction of machine learning models on singleplant omics data to unravel how plant rhizobial and PGPR gene expression in soybean nodules influence the performance of the top soybeanrhizobia combination in the field.
Profile
- You have a MSc degree in Bioengineering Biotechnology Computational Biology or Bioinformatics.
- You have a solid background in plant biology statistical data analysis machine learning R and Python programming
- Experience with plant field trials is a plus
- You are fluent in English (spoken and written).
- You can work in a team as well as independently.
- You are meticulous wellorganized responsible and selfcritical.
- You take pride in delivering highquality work.
- You have a passion for science and you can think outside the box.
We offer
- An exciting work environment in both a top basic research institute (VIB) and a top applied research institute (ILVO).
- The opportunity to be part of a dynamic interdisciplinary and international team.
- A challenging project with high societal value.
- Ample opportunity to learn new skills.
- An attractive salary.
Please complete the online application procedure and include a detailed CV a letter of motivation and the contact details of two referees. Applications are accepted until the position is filled.
For more information contact Steven Maere () and Hilde Muylle ().
Employment Type
Full Time
