i3WaterS › Doctoral positions

Intelligent data analysis tools to facilitate smart health assets assessments of critical urban water infrastructures using GPR

Description

Research Objectives

The main research goal of iWaterS is to provide, for the first time, rational analyses and explainable intelligent decision support of WDS to increase resilience to day-to-day incidents and to extreme events in the context of climate change such as floods or droughts, through new interdisciplinary and integral approaches for exploiting datasets (on-line, off-line), intelligent models (data-driven, numerical) and simulation results (digital twins, multiagent systems).

The specific research objective of this offer is To develop Artificial Intelligence methods for the automated interpretation of Ground Penetrating Radar (GPR) images, enabling reliable, non-destructive assessment of buried drinking water infrastructure and early detection of leak-related failures.

The candidate has the following subobjectives:

Objectives:

1) Collect evidence of water leakage using the GPR as a ND method to generate a repository of GPR images allowing development/training and validation of semi-autonomous/autonomous, identification and characterization tools based on intelligent systems.

2) Design/develop, implement and validate novel technological solutions to improve the interpretability of GPR images in leaking situations. This will generate novel approaches to achieve semiautonomous identification/characterization protocols to assess WDSs, while reducing the dependence on experts in the interpretation of GPR images.

Expected Results:

1) New Hub of GPR images of failed WDS components (in particular pipes leaking water) and,

2) a new semi-autonomous/autonomous intelligent GPR interpreter in the form of methodological tools (approaches, algorithms).

Requirements

Education level

Master Degree

Skills / Qualifications

• Experience (or interest) in urban water sector, including research, industry or public sector.
• Experience (desirable) in the use of tool for analysing data; e.g. Phyton, MatLab, R or Java or related programming languages
• Experience (desirable) in intelligent data analysis; e.g. Machine Learning and Data Mining, Knowledge-Based Systems, Data-driven models, Explainable Artificial Intelligence (XAI), Multi-Agent Systems, Decision Support Systems, Python, R, Data integration and/or interoperability.
• Documenting in Latex
• Ability to work as part of a team, including collaboration with other disciplines but also independently.
• The candidate is expected to publish her/his research in scientific journals and conferences.
• Strong organizational skills.

UCD is committed to equality, diversity and inclusion. Learn more: www.ucd.ie/equality

Required languages

• Excellent communication skills in English, particularly in relation to report writing and delivering presentations. Further details on the UCD’s minimum English language requirements can be found at http://www.ucd.ie/registry/admissions/elr.html
• (Desired) Knowledge of or willingness to learn other languages ​​in particular those associated with your secondments (i.e. Spanish).

Required languages

English – C1