PhD Research Fellow in Automated Industrial Battery Disassembly based on Robotics and Artificial Intelligence
Deadline: 02.06.2020
University of Agder
The University of Agder has more than 1400 employees and 13 000 students. This makes us one of the largest workplaces in Southern Norway. Our staff research, teach and disseminate knowledge from a variety of academic fields. Co-creation of knowledge is our common vision. We offer a broad range of study programmes in many fields. We are situated at two modern campuses in Kristiansand and Grimstad respectively.
We are an open and inclusive university marked by a culture of cooperation. The aim of the university is to further develop education and research at a high international level.
About the position
A 100 % position is available at the University of Agder, Faculty of Engineering and Science as a PhD Research Fellow in Mechatronics, affiliated to the Department of Engineering Sciences and the Mechatronics group, for a period of three years, or four years with 25% required duties. The position is located, at the present, at Campus Grimstad. The starting date is negotiable with the Faculty.
Responsibilities
The PhD Research Fellow will be associated with the Top Research Centre Mechatronics at the University of Agder in the application area of Battery Recycling, which includes Industrial IT, Robotics & Vision and Artificial Intelligence. Some of the industrial partners and collaborators in the project are – Norsk Hydro, BatteriRetur, Northvolt, University of Alder.
Mainly driven by electrical vehicles on the short term, and stationary and marine applications on the longer term, the upcoming industrial battery wave will be followed in the next 5 years by a second one, namely End of Life battery. In order to address the resource management challenges and to transition towards a circular economy, the fully automated dismantling of battery pack to cell level in support of reuse and/or recycling is required. A major challenge concerns handling a large variation of products and their conditions at End of Life. The PhD candidate will work on the design and implementation of a fully automated dismantling of industrial batteries.
The PhD candidate is expected to contribute in the following:
Based on multi-sensor and computer vision solutions and applying recent advances in machine learning algorithms for object recognition (e.e. YOLO R-CNN, 3D-CNN, voxnet, GCN/GNN and related other algorithms), develop solutions for perception and object recognition (identification and pose estimation).
Develop solutions that autonomously generate the optimal dismantling strategy.
Include self-learning abilities based on process and human feedback in order to increase robustness (e.g. to disassemble unknown batteries)
Develop 3D motion planning with collision avoidance, robotic grasping, and robotic manipulation to execute the disassembly operations. (e.g. unscrew, cut, pick-place, etc.)
Real-time and Offline data processing and monitoring
Conceptual approaches will be combined with experimental validation on a lab scale.
The position is connected to the subject area Computer Vision, Cognitive Robotics, Control, Motion Planning and Artificial Intelligence.
Required qualifications
The candidate is expected to hold a Master’s degree in Mechatronics, or similar, with completed courses in control systems, computer science, mechatronics, robotics, sensors fusion and algorithm development.
To be considered for this position, applicants must have either already finished their Master’s degree during the last five years or have a date for the defense of the Master’s thesis that will take place not later than an application due date.
Good communication skills and a good command of English are required. Applicants from some countries must document their English proficiency through an English test (TOEFL, IELTS or CEFR). Please check this website to see if an English test is required.
Applicants will be assessed on the basis of academic background and results, and any previous research and development work. Relevant industrial experience, personal suitability and good teamwork skills will also be emphasized.
Desired qualifications
Solid background in Machine Learning and Artificial Intelligence;
Knowledge in geometric convolution neural networks and deep learning;
Expertise and experience in 3D vision, i.e. working with point-cloud data, integration and data acquisition;
Expertise and experience in Robotics Operation System (ROS);
Experience with programming in Python, C/C++, Labview, MATLAB, and/or Java;
Expertise and experience in robots' control, path planning and object localisation, adaptive and cognitive systems.
Basic Scandinavian language skills are considered an advantage, but not a requirement
Personal qualities
A great learner, motivated and dedicated to research
Strong analytical and experimental skills
Team player, and be able to work independently depending upon the situations
Good communication and documentation skills (natural writer)
Personal qualities and suitability for the position will be emphasised.
We offer
Professional development in a large, exciting and socially influential organisation
A positive, inclusive and diverse working environment
Modern facilities and a comprehensive set of welfare offers
The position is remunerated according to the State Salary Scale, salary plan 17.515, code 1017 PhD Research Fellow, NOK 479 600 gross salary per year. A compulsory pension contribution to the Norwegian Public Service Pension Fund is deducted from the pay according to current statutory provisions.
General information
UiA is an open and inclusive university. We believe that diversity enriches the workplace and makes us better. We, therefore, encourage qualified candidates to apply for the position independent of gender, age, cultural background, disability or an incomplete CV.
Women are strongly encouraged to apply for the position.
The successful applicant will have rights and obligations in accordance with the current regulations for the position, and organisational changes and changes in the duties and responsibilities of the position must be expected. The engagement is to be made in accordance with the regulations in force concerning the acts relating to Control of the Export of Strategic Goods, Services and Technology. Appointment is made by the University of Agder’s Appointments Committee for Teaching and Research Positions.
Short-listed applicants will be invited for interview. With the applicant’s permission, UiA will also conduct a reference check before appointment. More about the employment process.
In accordance with the Freedom of Information Act § 25 (2), applicants may request that they are not identified in the open list of applicants. The University, however, reserves the right to publish the names of applicants. Applicants will be advised of the University’s intention to exercise this right.
Application
The application and any necessary information about education and experience (including diplomas and certificates) are to be sent electronically. Use the link "Apply for this job".
The following documentation must be uploaded electronically:
Certificates with grades
Master’s thesis
References
Academic work and R&D projects, as well as a list of these
Project description with a maximum scope of 5 pages, including reference list. The outline should present and discuss possible research questions, theory perspectives, material, a progress plan, and methods within the given framework
Any other relevant documentation
The applicant is fully responsible for submitting complete digital documentation before the closing date. All documentation must be available in a Scandinavian language or English.
Application deadline: 02.06.20
Contact
For questions about the position:
Associate Professor Martin Choux, tel. +47 37 23 34 45, e-mail martin.choux@uia.no
