Deadline:

28 October 2019.

Location:

Australia.

(Partially Funded)

Description

Advanced autonomy for unmanned vehicles – Ph.D. scholarship

The doctoral student will work in the intersection of the areas of robotics and automatic control. We are looking for a qualified and enthusiastic PhD student who wishes to investigate the embedded guidance, control, and navigation algorithms (e.g., model predictive control, adaptive control, and concurrent learning) for unmanned ground vehicles.  We aim to leverage the current state-of-the-art autonomy level towards smarter robots, which can learn and interact with their environment, collaborate with people and other robots, plan their future actions, and execute the given task accurately.

More Details

Nowadays, the complexity in the design of robotic systems increases enormously since human beings desire a higher level of intelligence and autonomy. The developed systems must be capable of autonomously adapting to the variations in the operating environment while maintaining the overall objective to accomplish tasks even in highly uncertain and unstructured environments. Such robotic systems must display the ability to learn from experience, adapt themselves to the changing environment, and seamlessly integrate information to-and-from humans.

Opportunity Focus Areas:

  • Mechanical Engineering
  • Mechatronics Engineering
  • Electrical Engineering
  • Computing

Required Languages

English.

Eligible Countries

ALL WORLD COUNTRIES.

Program Period

  • 3 years with the possibility of two 6-month extensions in approved circumstances.

Eligibility Requirements (Criteria)

  • To be eligible, you must meet the entry requirements for a higher degree by research.
  • Hold a Master degree in Mechanical, Mechatronics, Electrical Engineering or related fields.
  • The strong background in control theory and robotics.
  • Excellent verbal and writing skills in English with very good communication skills, for more details about language requirements Here.
  • Experience in model-based control theory (Preferred).
  • Hands-on experience in robotic systems (Preferred).
  • Experience in Robot Operating System (ROS) (Preferred).
  • Concrete knowledge in C/C++ or Pyton (Preferred).
  • Demonstration of research activities (conference or journal papers) (Preferred).

Opportunity Cost

(Partially Funded)

  • $28,092 per annum tax-free (2020 rate), indexed annually.

How to Apply

First Step: Before you apply

  • .Check your eligibility Here
  • .Prepare your documentation Here
  1. .A detailed Curriculum Vitae
  2. A motivation letter, including a brief description of past .experience
  3. Copies of diploma and transcripts of Bachelor and Master degrees.
  4. At least three references are available to contact.
  5. A copy of your Passport.
  6. Evidence for meeting UQ’s English language proficiency requirements (which must be valid at commencement date).

Second Step:

  • Create your account and Fill the application From Here.
  •  Please ensure that you:
  1. Select ‘I am applying for, or have been awarded a scholarship or sponsorship’.
  2. Enter in the free-text field ‘AAUV’.
  3. list the enrolling unit as the School of Mechanical & Mining Engineering.
  4. Enter Dr. Erkan Kayacan as your supervisor.

Note:

  • You can save draft of application and contain it later.
  • For more details about applying Here.

Apply Now

More Details

Know more about this opportunity:

Official Website

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To learn how to write CV, Essays, Personal statement,  and know about recommendation letters click here:

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This Scholarship Published by:
Ahmed tarek / Egypt

Reviewed by “ Mariam Mohamed Kamal / Egypt

& “ Hanine Aymen / Egypt
MARJ3 Intern
MARJ3 Scholarships team