PhD Research Fellow - Collective Deep Learning and Networked Control for Multiple Collaborative Robot Systems
Deadline: 15.03.2021
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
The Faculty of Engineering and Sciences at University of Agder (UiA) has a PhD position available within the fields of Artificial Intelligence, Deep Learning, Cooperative control and Robotics. The position is within the Norwegian Research Council’s Long-term research project "Collective Efficient Deep Learning and Networked Control for Multiple Collaborative Robot Systems (DEEPCOBOT)". The PhD position is located at Campus Grimstad, affiliated to the Department of Information and Communication Technology, for a period of 3 years with the possibility of extensions based on additional teaching assistance duties. The position is scheduled to start in June 2021, but it is negotiable with the Faculty.
Description
The overall goal of the DEEPCOBOT project is the design of a new generation of decentralized data-driven deep learning-based controllers for multiple coexisting collaborative robots (cobots), which can interact both between themselves and with human operators in order to collectively learn from each other’s experiences and perform cooperatively different complex tasks in a large-scale industrial process environment. The project is motivated by the increasing demand of automation in industry, especially the demand of a safer, more intuitive, more comfortable and more efficient collaboration between multiple cobots and human operators to integrate the best of human abilities (creativity, adaptivity, interaction) and robotic automation (speed, reliability, precision and inexhaustible task execution capability), while being robust across different environments and human operators. This project will lead to several important advances in the areas of machine learning, decentralized shared control for cobots, graph signal processing, design of cross-layer network protocols for distributed computation and collective intelligence across multiple cobots.
The PhD position will cover theoretical advancements, algorithm design, as well as simulation and experimental evaluation, on the following research topics:
1) Decentralized local controllers at the cobots using the Deep Reinforcement Learning framework, where each cobot learns both from its local information and from other information about other cobots’ learning process in the neighborhood.
2) Deep learning algorithms for the cobots to infer and predict the motion of human operators interacting with them, including also interpretable, active and transfer learning methods to speed up the learning process and the corresponding shared control strategies guiding the interaction between the cobot and human operators.
3) Graph signal processing algorithms, graph neural Networks and cross-layer network protocols to provide the required diffusion of information across the cobots so that both the deep learning process is efficient and stable, and the testing running phase is also executed correctly, satisfying the real-time and safety constraints, and minimizing energy consumption.
The project will be integrated in two Centers at UiA, namely, the NFR-Toppforsk funded WISENET Center and the Center of Mechatronics at UiA, where the PhD student will benefit intellectually from the interaction with internationally recognized researchers, well-equipped environments and will build on and strengthen the established cooperation in AI, Machine Learning, industrial robotics, and autonomous networked cyber-physical systems with industry partners, such as ABB Norway, Mechatronics Innovation Lab (MIL), Omron Electronics Norway, and international partners including University of California San Diego (USA), KTH Royal Institute of Technology (Sweden) and the University of Navarra (Spain). The project will give also the opportunity to pay extended visits to Universities in USA, Sweden and Spain.
Required qualifications
To be regarded as an eligible applicant, the candidates must have:
A solid academic background with a MSc. degree in either of these: ICT, Mechatronics, Electronics Engineering, Electrical Engineering, Computer Science, Computer Engineering, or other related disciplines with a grade of B or better in terms of UiA’s grading scale (or equivalent), is required.
Applicants must have either already finished their Master degree during the last five years or have a date for the defense of the Master Thesis that will take place not later than March 2021.
Substantial knowledge of the following:
Systems and Control
Machine Learning techniques
Advanced Optimization techniques
Robotics
Wireless sensor networks and cyber-physical systems
Statistical signal processing
Robot operating system (ROS)
Mathematical analysis and linear algebra
Programming in Python, Matlab, C/C++.
English proficiency, both written and oral. International candidates that are not exempt from the English language requirements pursuant to the guidelines of the Norwegian Agency for Quality Assurance in Education (NOKUT) must document this through one of the following tests with the stated results or better:
TOEFL - Test of English as a Foreign Language with a minimum score of 600 for the Paperbased Test (PBT), or 92 for the Internet-based Test (iBT)
IELTS - International English Language Testing System, with the result of 6.5
The candidates can also demonstrate their fluency in English during interview.
Information about why UiA provides an excellent working environment can be found here.
The position is remunerated according to the State Salary Scale, salary plan 17.515, code 1017 PhD Research Fellow, NOK 482 200 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 other necessary information about education and experience (including diplomas and certificates) are to be sent electronically only. Use the link "Apply for this job".
The following documentation should be submitted as attachments to the online application:
A research statement (maximum 4 pages) including:
a justification of the background of the candidate for the requirements of the position (see description above about the required knowledge areas).
an outline of applicant’s research interests in line of the research topics of this position.
a short presentation of the motivation of the applicant
a tentative research proposal related to the proposed project, meeting the above research objectives.
Certificates and transcripts for the Bachelor’s degree and Master’s degree, with a summary of the courses/subjects included in the degree.
Applicants with a foreign higher education must attach an official description of the grading system used at the issuing institution.
Applicants who are required to document their English proficiency must submit their TOEFL or IELTS test results (these may be forwarded after the closing date) or their CEFR certificate.
Names and contact information of two reference persons
List and links to applicant's scientific publications (if any)
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.
