Job description

The water sector is under increasing pressure worldwide. To ensure water security and sustainable development, major paradigm shifts are in progress. A first important shift is the transition towards a circular water and resource economy. This transition is inherently a multidisciplinary and multi-objective effort that implies bridging historical silo’s (for example drinking water, wastewater, hydrology for rainwater harvesting, agriculture, industry).
The second paradigm shift is the digital transformation and the emergence of powerful and automated model simulations that support real-time smart decision making.

However, to achieve powerful digital tools that can support holistic decision making towards more circular and sustainable water management, many different data sources, models and submodels need to communicate with each other in a more efficient and automated way.
For example, the development of a digital twin for water management in a city requires heterogeneous sources of data (e.g., water quality, energy, cost, meteorology, etc.) and various models/sub-models (e.g., models for sewer networks, hydrology, river hydraulics, water/wastewater treatment technologies, economic models, etc.) of the system to be connected to each other and communicate in an efficient and automated manner.

WaterFRAME (Water Fit for Reuse Architecture and Modelling Ecosystem) is a FWO Strategic Basic Research (SBO) project that aims at developing an interoperable holistic digital framework for the water domain that is able to bridge historical data and modelling silo’s to support high-level decisions on water management. The WaterFRAME decision support system will be realized through standardized data formats and the concept of ontologies (a conceptual structure of a domain of interest including all objects and the semantic relationship between them). A library of ontologies will be developed based on specific use cases that encompasses all data, information, models, parameters,... within the water reuse domain. Data and models will be then mapped onto the ontologies to create knowledge graphs which allows to create a flexible, interlinked and dynamic data representation of the real-world which can serve as a digital twin of the system under study. An optimization layer will be developed on top of the dynamic knowledge graph that will interact with the domain ontologies to provide support for decision making through data extraction, analysis, model simulations and automatic optimization. The knowledge graph will moreover be augmented with environmental indicators through LCA analysis.
The methodology developed within WaterFRAME will be applied to 3 use cases with in-silico and real datasets for a proof of concept implementation of the holistic decision making framework.

In this position, you will be working in a dynamic research group and will be actively involved in the state-of-the-art research on mathematical modelling, integrated asssement and interoperability. In particular, you will contribute to development of an ontology model of the water reuse domain within the context of the WaterFRAME project as well as a dynamic knowledge graph that will serve as the input for an optimization layer (developed within another work package of the project) to provide quantitative indicators for holistic decision making.

Your specific tasks include:

• You will conduct a literature review on the existing ontologies and semantic models for the water and water-related sectors at local and global levels.
• You develop ontologies for the water reuse domain such as ontology for rain water collection and storage, ontology for treatment processes, ontology for water reuse cases (e.g., wastewater effluent, drinking water, gray water), ontology for mathematical models within the water reuse domain.
• You develop a library of interconnected ontologies based on the one developed in the previous task.
• You develop methodologies for alignment of the ontologies with the aim of checking for semantic, syntactic and structural heterogeneity. You will investigate the use of machine learning algorithms for automatic ontology alignment.
• You will construct a dynamic knowledge graph by mapping sample (virtual and real) datasets to the library of ontologies and test the ontology model for different case studies..
• You will collaborate closely with the project partners, gathering knowledge needed for development of a comprehensive and relevant library of ontologies.
• You write down the results in scientific articles and a PhD thesis.

Job profile

AS THE IDEAL CANDIDATE

• You have a master’s degree in computer science or in an engineering field (e.g. bio-science, chemical, process) with strong track record in modelling and computer programming
• You have solid experience with computer programming (such as Python/Julia/C/C++/etc) including object-oriented programming paradigm
• You have good knowledge of mathematical modelling, data analysis and machine learning or a strong affinity to learn
• Background in semantic data models is a plus
• Knowledge in modelling and integrated assessment of water and wastewater systems is a plus
• You like a challenge and are not afraid to learn and explore new methodologies
• You are a quick learner and are able to conduct independent research
• You are fluent in English, both speaking and writing
• You are motivated and dedicated
• You are a team player
  
  

WHAT WE CAN OFFER YOU

• We offer you a full-time, joint PhD contract between Ghent University and Université Laval of definite duration for the period from 01/11/2023 to 31/10/2027
• A joint PhD gives you the opportunity to work and grow in 2 renowned international research groups on water modelling and will lead to a double PhD degree. You are expected to spend at least 1 year in each host institution over the course of your PhD.
• About Ghent University: Ghent University is a world of its own. Employing more than 8,000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest, most exciting employers in the area and offers great career opportunities. With its 11 faculties and more than 80 departments offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students.
• About Université Laval: Université Laval is an entire community in the heart of Quebec City, a complete university recognized for its leadership and its culture of excellence in both teaching and research. The Department of Civil Engineering and Water Engineering is composed of 22 professors working in the areas of water and environment, geotechnics, and structures and materials. The department hosts research and teaching Chairs, research centers, and internationally recognized research groups.
• Salary is determined according to the UGent salary scales.
• Moreover, you can enjoy a number of benefits, such as a wide range of training and education opportunities, 36 days of holiday leave (on an annual basis for a full-time job) supplemented by annual fixed bridge days, bicycle allowance and eco vouchers.

How to apply

Your application must include the following documents:

• Your CV: an overview of your publication list and your study results (merged into one pdf file)
• A Cover letter: your application letter in pdf format (describe your values and provide examples relevant to the job description)
• Diploma: a transcript of the required degree (if already in your possession). If you have a foreign diploma in a language other than our national languages (Dutch, French or German) or English, please add a translation in one of the mentioned languages.
  
  

As Ghent University maintains an equal opportunities and diversity policy, everyone is encouraged to apply for this position.

Please send your complete applications by email to Prof. Elena Torfs (elena.torfs@gci.ulaval.ca) and Dr. Saba Daneshgar (saba.daneshgar@ugent.be).