Predicting failure in crystalline materials using machine learning techniques
Unknown, United Kingdom
This course explores the application of machine learning techniques to predict failure in single-crystal materials used in various components, from micro-lenses and MEMS devices to large turbine blades. It emphasizes the integration of crystal plasticity models with advanced computational frameworks and small-scale nano-micro indentation experiments to enhance failure prediction accuracy in complex geometries and loading conditions, ensuring safety and reliability in industrial applications.
- Unknown, United Kingdom
- 3 years
- On Campus
- ₹32,82,675/Year
Pros & Cons
Not enough reviews to generate pros and cons
Program Overview
This course explores the application of machine learning techniques to predict failure in single-crystal materials used in various components, from micro-lenses and MEMS devices to large turbine blades. It emphasizes the integration of crystal plasticity models with advanced computational frameworks and small-scale nano-micro indentation experiments to enhance failure prediction accuracy in complex geometries and loading conditions, ensuring safety and reliability in industrial applications.
QS World Ranking
Not Available in Not Available
Class Size
400 Students
Key Features
Specializations Available
AI/ML, Systems, Theory, Human-Computer Interaction
Research Opportunities
Access to cutting-edge research labs and industry partnerships
Admission Requirements
TOEFL®
92.0
Key Dates
Application Start time & Deadline
Starting 2025-07-01
Apply before 2125-04-18
Starting 2026-04-01
Apply before 2125-04-18
Starting 2026-01-01
Apply before 2125-04-18
Starting 2025-10-01
Apply before 2125-04-18
Program Start
Sep 2025
Programme Structure
To obtain additional information about the program, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.Check out the full curriculumVisit programme website
Program Highlights
- Comprehensive curriculum covering all key topics
- Hands-on projects and real-world case studies
- Expert faculty with industry experience
- Career support and placement assistance
Academic Requirements
GPA
3.5
English Language Requirements
TOEFL®
92.0
Overall ScoreAdditional Requirements
Applicants should possess or expect to achieve a minimum of a 2:1 (or equivalent) in any engineering, physics, or mathematics degree. Necessary application materials include an academic transcript detailing modules and grades, a degree certificate if already graduated, a personal statement outlining motivation, relevant skills, and career goals, and a research proposal if applicable. These documents should demonstrate relevant academic background and motivation for the programme.
Course Fees
₹32,82,675/Year
Annual Fee
3 years
Total Duration
Living Costs
No Living costs available.
University Scholarships
No University Scholarships Available
External Scholarships
Rochelle Nicolette Perry Memorial Scholarship
N/A
Amount
1250 USD
Deadline
Not specified
Organization of American States (OAS) Academic Scholarship Program
N/A
Amount
Various benefits
Deadline
Not specified
Master's Scholarship
N/A
Amount
Various benefits
Deadline
Not specified
Denise Halbach Performance Scholarship
N/A
Amount
2000 USD
Deadline
15 Apr 2025
Thomas Jefferson Prize in United States History
N/A
Amount
300 EUR
Deadline
Anytime
Eligibility Requirements
No Eligibility Requirements Available
Application Process
No Application Steps Available
News About Abroad
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