PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26

Eligible Degrees:

PhD

Funding Type:

Partial Funding, AUD 33,826

Deadline:

31 Dec 2026

Eligible Courses:

Science or Engineering

Eligible Nationalities:

Open to all nationals

Scholarship can be taken at:

  • RMIT University, Melbourne City campus
  • Updated on: 25 Oct, 2024

     

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    Details about PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26

    PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 is offered for PhD degree in the field of Science or Engineering. You can apply to this scholarship here. The deadline for the sending your application is 31 Dec 2026. This scholarship is provided by RMIT University, Melbourne City campus and the value of this scholarship is Partial Funding, AUD 33,826 . This scholarship is open for: Open to all nationals.

    • Deadline: 31 Dec 2026
    • Scholarship value: Partial Funding, AUD 33,826

    The project will use deep learning and artificial intelligence to assess the structural integrity and forecast the fatigue life of aircraft metal alloys that are additively produced.

    Eligibility criteria:

    To be eligible, applicants must:

    • Have a Master by Research degree; or
    • Have a Master by Coursework degree with a significant research component graded as high distinction or equivalent; or
    • Have a Bachelor Honours degree achieving first-class honours in Engineering (Aerospace, Mechanical, Materials, Manufacturing), Science (Physics, Chemistry), or a related field.

    Application process:

    To apply, submit the following documents to Professor Raj Das (raj.das@rmit.edu.au):

    • A cover letter outlining interest in the project
    • Evidence of research ability, such as a digital copy of a Master’s or Honours’ thesis
    • A digital copy of academic transcripts
    • A CV including any education, marks/grades, relevant professional experience, publications (if any), awards (if any), and names of two referees.

    Benefits:

    Eligible applicants will get a scholarship of $33,826.

    Source : RMIT University, Melbourne City campus
    Disclaimer: All Content, Logo and Company names are registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.

    FAQs

    1. Can I get an education loan to study abroad at RMIT University, Melbourne City campus

      Yes, you can secure an education loan to study abroad at RMIT University, Melbourne City campus. Education loans are of two types- Collateral and non collateral. Collateral includes either: Immovable property – a house or a flat or land (or) liquid security – an FD, or LIC or shares or bonds. Agricultural lands are not accepted by any bank for education loan.

      Public banks like SBI, BOB offer these types of education loans. There are many NBFCs who offer Non-collateral education loans. Apply for the best education loan to study abroad.

    2. When is the deadline of PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26?

      The deadline of PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 is 31 Dec 2026

    3. For which degree is PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 offered for?

      PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 is offered to PhD degree

    4. For which field is PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 offered for?

      PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 is offered for Science or Engineering

    5. Who can apply for PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26?

      PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 is open for: Open to all nationals

    6. Who is offering PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26?

      PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 is offered by RMIT University, Melbourne City campus

    7. What is the funding covered in PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26?

      PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 Covers Partial Funding, AUD 33,826

    8. Where can PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 can be taken at?

      PhD scholarship in Structures and Materials: Defect Analysis and Fatigue Life Prediction in Additively Manufactured Alloys using Machine Learning at RMIT University 2024/26 can be taken at
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