Phd Candidate in Machine Learning
About the position
Are you passionate about engaging in doctoral level research to solve scientific problems within the area of Reinforcement Learning and Optimal Control, a topic with great industrial significance? If yes then this position may be for you. This exciting research project will be carried out at the Department of Engineering Cybernetic (https://www.ntnu.edu/itk), in close collaboration with the NTNU Artificial Intelligence initiative, and the Dept. of Computer Science. The research will be performed under the supervision of Prof. S. Gros and his colleagues.
Machine Learning (ML) is increasingly used in control applications. E.g. the early successes in Autonomous Driving are partially due to substantial progresses in ML. A number of other applications, mostly in robotics and autonomous systems are benefitting from these developments. Within ML, Reinforcement Learning (RL) is a specific class of techniques that deals with the optimal control of dynamic systems. RL has attracted a lot of academic and public attention lately by beating masters in Chess and Go games. Despite its early successes, the current state-of-the-art in RL suffers from some drawbacks, making it difficult to introduce in industrial applications. In this PhD project, we will investigate and develop novel ideas combining RL, optimal control and Model Predictive Control in order to address some of the deficiencies in the field. You will carry out research on this topic in collaboration with Prof. S. Gros and his colleagues. The focus will be on theory and simulations, but some laboratory experiments are possible.
The PhD-position's main objective is to qualify for work in research positions. The qualification requirement is completion of a master’s degree or second degree (equivalent to 120 credits) with a strong academic background in Control, Optimization and Machine Learning or equivalent education with a grade of B or better in terms of NTNU’s grading scale. Applicants with no letter grades from previous studies must have an equally good academic foundation. Applicants who are unable to meet these criteria may be considered only if they can document that they are particularly suitable candidates for education leading to a PhD degree.
The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and national guidelines for appointment as PhD, post doctor and research assistant.
Other required qualifications:
- Strong background in MPC, Optimal Control, and Reinforcement Learning
- Strong mathematical skills (systems dynamic, probability and statistics, optimization theory)
- Excellent Matlab or Python programming skills
- Excellent written and oral English skills
- Strong analytical skills, synthetic, capable of handling and expressing complex ideas easily
- Strong capabilities for abstract and mathematical thinking
- Resilient and ambitious, self-motivated
- Team player, good at collaborating, respectful
- Resourceful, autonomous and independent
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability, in terms of the qualification requirements specified in the advertisement
- exciting and stimulating tasks in a strong international academic environment
- an open and inclusive work environment with dedicated colleagues
- favourable terms in the Norwegian Public Service Pension Fund
- employee benefits
Salary and conditions
PhD candidates are remunerated in code 1017, and are normally remunerated at gross from NOK 449 400 before tax per year. From the salary, 2 % is deducted as a contribution to the Norwegian Public Service Pension Fund.
The successful candidate will be appointed for a period of 3 years, with possible extension to a fourth year if the candidate undertakes teaching related duties.
Appointment to a PhD position requires admission to the PhD programme in Eng. Cybernetic (https://www.ntnu.edu/studies/phtk). As a PhD candidate, you undertake to participate in an organized PhD programme during the employment period. A condition of appointment is that you are in fact qualified for admission to the PhD programme within three months.
Appointment takes place on the terms that apply to State employees at any time, and after the appointment you must assume that there may be changes in the area of work.
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background. Under the Freedom of Information Act (offentleglova), information about the applicant may be made public even if the applicant has requested not to have their name entered on the list of applicants.
Publications and other academic works that the applicant would like to be considered in the evaluation must accompany the application. Joint works will be considered. If it is difficult to identify the individual applicant's contribution to joint works, the applicant must include a brief description of his or her contribution.
Please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates. Applicants invited for interview must include certified copies of transcripts and reference letters.
Please refer to the application number 2019/4040 when applying.
Application deadline: 01.04.2019.
NTNU - knowledge for a better world
The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.
Department of Engineering Cybernetics (ITK)
Engineering cybernetics is the study of automatic control and monitoring of dynamic systems. We develop the technologies of tomorrow through close cooperation with industry and academia, both in Norway and internationally. The Department contributes to the digitalization, automation and robotization of society. The Department of Engineering Cybernetics is one of seven departments in the Faculty of Information Technology and Electrical Engineering.
Employer NTNU - Norwegian University of Science and Technology
Place of service Gløshaugen