About the Project
Plant-based dairy and meat alternatives have grown in popularity in recent years for various reasons, including sustainability and health benefits, as well as lifestyle trends and dietary restrictions. However, plant-based food products can be nutritionally unbalanced, and their flavour profiles may limit their acceptance by consumers. Microorganisms have been used in making food products for millennia. However, the diversity of microbial communities driving plant-based fermentations, as well as their key genetic and phenotypic traits and potential synergies among community members, remain poorly characterised. Many data exist, but they are spread into different literature (scientific and grey) or, in the best case, in different databases. However, they are not always reusable because they are difficult to find and access and because databases are not systematically interoperable.
The FAIROmics initiative, an interdisciplinary research programme, will gather universities, research centres and private companies to enable the FAIRification of omics data and databases interoperability and develop knowledge graphs for data-driven decision-making to rationally design microbial communities for imparting desirable characteristics to plant-based fermented foods in the context of open science and its regulations. The FAIROmics training programme aims to develop doctoral candidates’ skills at the interface between artificial intelligence, life sciences, humanities, and social sciences.
Application deadline: 15/05/2024 23:59 – Europe/Brussels.
Envisaged job starting date: October 2024.
Hosting organisation: INRAE Jouy-en-Josas, (MaIAGE),
Planned secondment: University of Szeged (USZ) for a duration of 12 months.
Please note that this PhD position will lead to the award of a double diploma after the completion of a stay in each of these organisations: The University of Paris-Saclay (UPSaclay), France and the University of Szeged (USZ), Hungary.
Offer description:
We are looking for one Doctoral Candidate to join our project at multiple sites in the EU with a master’s degree in a relevant discipline (Master’s degree in engineering, physics, systems biology, applied mathematics, biotechnology) interested in modelling, analysis and control of biological systems in the context of microbial fermentations. The PhD project aims to develop information extraction (IE) methods to automatically produce a knowledge graph about microbe biology involved in plant-based food transformation or preservation. The knowledge graph will formalise the molecules produced and degraded by microorganisms in the fermentation process.
The IE methods will involve named-entity recognition, entity normalisation with respect to semantic references and relationship extraction. They will be based on the most recent deep learning approaches that train language models using few or no training examples by transfer learning or exploiting existing structured information, i.e. knowledge bases and ontologies for distant or weak learning by including relevant information according to the needs of the FAIROmics dedicated use cases (e.g. NCBI Taxonomy for taxa, FoodEX2 for food, ChEBI for molecules, KEGG for pathways). Existing annotated corpora will serve as a starting point for training (e.g. CHEMDNER, Pathway Curation, Bacteria Biotope). The project will rely on existing tools and resources on microbe biology developed by MaIAGE partners (e.g. Omnicrobe application*, Ontobiotope ontology*, extraction workflow).
The PhD student will design and evaluate original machine-learning-based methods for extracting information on plant-based fermentation metabolism from text. The models and software will be available to the scientific community in an open-source license. The extracted knowledge will feed a publicly available knowledge graph of microbial properties. The results will be published in the major NLP venue and relevant bioinformatics journals.
We offer:
*family = be married/be in a relationship with equivalent status to a marriage recognised by the legislation of the country or region where it was formalised/have dependent children who are being maintained by the researcher.
* EXCLUDED: short stays such as holidays, compulsory national services such as mandatory military service and procedures for obtaining refugee status under the General Convention.
Recruitment process:
For more information about the offer, the project and the recruitment process, please visit our website.
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