Publisher
source

Mohammad Aminpour, Ph.D.

1 year ago

AI-Driven Reliability Assessment in Infrastructure Geotechnical Engineering RMIT University in Australia

Degree Level

PhD

Field of study

Machine Learning

Funding

Full funding available

Deadline

December 31, 2026
Country flag

Country

Australia

University

RMIT University

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Where to contact

Official Email

Keywords

Machine Learning
Environmental Science
Environmental Engineering
Artificial Intelligence
Renewable Energy
Geotechnical Engineering
Python Programming
Finite Element Method
Limit Analysis
Finite Element Analysi
Computational Modeling

About this position

**PhD Scholarship Opportunity: AI-Driven Reliability Assessment in Infrastructure Geotechnical Engineering - RMIT University, Melbourne, Australia**?? Are you passionate about geotechnical engineering and leveraging AI and machine learning to tackle real-world challenges in infrastructure geotechnics and renewable energy? We are excited to announce a full PhD scholarship opportunity at RMIT University, Melbourne, Australia for an innovative project focused on AI-driven reliability assessment in infrastructure geotechnics, specifically for slope stability and wind energy applications.**Project Overview:**?? This cutting-edge project aims to assess and manage multiple levels of uncertainty in geotechnics, including soil variability using random field theory and climate change impacts by considering storm event scenarios. By utilizing advanced machine learning techniques, we aim to significantly improve the efficiency of reliability assessments, reducing computational time and resources.**What We Offer:**?? Full PhD scholarship and fee waiver.?? Access to advanced research facilities and resources.????? Mentorship from leading researchers in the field.?? Support for professional development and career advancement.**Skills Desired:**??? Familiarity with computational modeling in geotechnics (e.g., finite element and limit analysis, using tools such as Optum).?? Programming skills (Python).?? Machine learning experience or a strong interest in this area is highly relevant.**Who We Are Looking For:**?? A highly motivated individual with a strong background in geotechnics, AI, or related fields.?? Excellent analytical and problem-solving skills.?? Ability to work independently and as part of a team.?? A track record of academic excellence.**How to Apply:**If you are interested, please fill out the Expression of Interest form below. https://lnkd.in/gYtDYwiHFeel free to contact me at [email protected] if you have any questions.#PhDScholarship #GeotechnicalEngineering #AI #MachineLearning #RenewableEnergy #ResearchOpportunity #HigherEd #Engineering #ScholarshipOpportunity

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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