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Fully funded PhD Position in Robotics - Automating the Process of Disassembly of Electrical Vehicle Battery Pack

University of Birmingham - School of Metallurgy and Materials

Qualification Type: PhD
Location: Birmingham
Funding for: UK Students, EU Students, International Students
Funding amount: A funded 3-year PhD studentship with a stipend of £15,285 per year (tax-free) is available to EU, Overseas (Non-EU), UK.
Hours: Full Time
Placed On: 23rd August 2021
Closes: 5th October 2021

A funded 3-year PhD studentship is available in the research group of Professor Rustam Stolkin at the Extreme Robotics Lab (ERL), at the University of Birmingham, with a stipend of £14,777 per year (tax-free).

This PhD project focuses on developing an automated framework for robotizing the process of dismantling the Electrical Vehicle (EV) Lithium-ion batteries. There are several tasks during the process of disassembly that should be executed under a hierarchical execution order in an unstructured environment. Some of the tasks can be performed manually by humans, some of them are more complex and require to be completed jointly by robot and Human (shared-control), and some of them could be completed fully autonomously by applying AI techniques.

This PhD project aims to integrate various manipulation and machine vision techniques in a modular and closed-loop format. This PhD project investigates explicitly the development of a sequence of automated disassembly actions. The project will be supervised by Professor Rustam Stolkin, Dr Alireza Rastegarpanah.

The PhD student has this opportunity to work closely with the researchers working on the RELIB project. In addition, the student has this opportunity to develop his/her automated framework at the Extreme Robotics Lab (ERL) using Cobots, and later transfers and applies the developed methods on heavy-duty robots located at The Birmingham Energy Innovation Centre (BEIC).

Eligibility:

Applications are welcome from home and international students.
The candidate must meet the English language requirements and have the required English certificate ready. Read more here.

Knowledge, Skills, Qualifications and Experience Required:

• The candidate will have a 1st Class Masters degree (or equivalent) in robotics, computer science, mechanical engineering or a relevant discipline.
• Having background in Machine Learning and Neural Networks.
• Demonstrable knowledge in computer vision, control and robotic manipulation
• Having experience in working with ROS
• Confidence and independence in programming in C++, Matlab, JAVA.
• Having experience in working with/controlling the redundant robot arms is an advantage
• Having experience in working with/controlling the industrial KUKA arms (KR500, KR20) is an advantage
• Having experience in using OpenCV, VISP, PCL and other relevant open-source libraries is an advantage
• Strong communication skills in English (both oral and written)

Application:

In order to apply for this PhD position, you need to do the following:
Please share the following documents on a cloud and email the link to Dr Alireza Rastegarpanah (a.rastegarpanah@bham.ac.uk):

• Cover letter summarising your research interests and suitability for the position;
• Two recommendation letters;
• A full curriculum vitae.

******* PLEASE DO NOT ATTACH THE REQUESTED DOCUMENTS TO YOUR EMAIL*******

The shortlisted candidates will be invited for the interview. Instruction for applying for this position will be given to the selected candidate once the interview process completed.

About the Extreme Robotics Lab

The University of Birmingham Extreme Robotics Lab, is one of the leading university robotics labs in Europe dedicated to practical applications of robotics and AI in extreme environments:

http://www.birmingham.ac.uk/research/activity/metallurgy-materials/robotics/index.aspx

The UoB robotics team are collectively working on robotic grasping and manipulation, planning and reasoning for fixed and/or mobile manipulators, robotic vehicles and navigation, robot dynamics and control, Computer Vision, machine learning and AI.

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