Ledig stilling ved UiT Norges arktiske universitet
PhD Fellow in Machine learning for UAV control
UiT The Arctic University of Norway
UiT is a multi-campus research university in Norway and the northernmost university of the world. Our central location in the High North, our broad and diverse research and study portfolio, and our interdisciplinary qualities make us uniquely suited to meet the challenges of the future. At UiT you can explore global issues from a close-up perspective.
Credibility, academic freedom, closeness, creativity and commitment shall be hallmarks of the relationship between our employees, between our employees and our students and between UiT and our partners.
Faculty of Engineering Science and Technology
The Faculty of Engineering Science and Technology, Department of Computer Science and computational engineering has a PhD position vacant for applicants who wish to obtain the degree of Philosophy Doctor (PhD). The position is attached to the research groups Simulations and Electromechanical systems.
The position is for a period of four years. The nominal length of the PhD program is three years. The fourth year is distributed as 25 % each year, and will consist of teaching and other duties. The work place is at UiT in Narvik.The objective of the position is to complete research training to the level of a doctoral degree. Admission to a PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position. The PhD candidate shall participate in the faculty’s organized research training, and the PhD project shall be completed during the period of employment.
The position's field of research
The position’s field of research is application of machine learning methods in modelling, multivariate analysis, guidance and nonlinear control of unmanned aerial vehicles, and multirotor platforms in particular. Control algorithms for multirotor systems has traditionally been developed through classical systems and control theory, but machine learning, and its subfield deep learning now offers new possibilities, and there is currently a push to unify the frameworks of traditional control theory and data-driven modelling and control. The problem with including machine learning methods in control systems is the resulting loss of transparency, and challenges in mathematical analysis to ensure stability and performance. Control systems with machine learning in the loop often lack stability proofs and performance guarantees, which are crucial if they are applied in safety-critical situations.
The purpose of this PhD project is to combine the expressive power of machine learning methods with the mathematical soundness of nonlinear control theory. The candidate will investigate methods for mathematical modelling and multivariate analysis of multirotor platforms in dual quaternion frameworks, and develop algorithms for guidance and control combining principles of machine learning with traditional nonlinear control theoretic tools.
The position’s affiliation
The position will be affiliated with the Department of Computer Science and Computational Engineering, and the PhD fellow will be part of both research groups Simulations and Electromechanical systems. The department is responsible for study programs related to computer science, as well as to applied mathematics and engineering design, with approximately 230 students. The department organizes most research activities under research groups, conducting fundamental and applied research in themes such as geometric modelling, numerical simulations, programming and visualization, artificial intelligence, machine learning and related areas.
For further information about the position available by contacting
- Associate professor Rune Dalmo, +4776966195, [email protected]
- Professor Raymond Kristiansen, +4776966196, [email protected]
The candidate must have a master’s degree in computer science, with a completed master’s thesis on a relevant topic. In addition, knowledge and training in the following fields are desirable:
- machine learning
- artificial intelligence and intelligent agents
- algorithms and programming
- guidance and control
- unmanned aerial vehicles
- attitude parameterization with quaternions
Technical skills in C/C++, Matlab, Python and GMLib is a prerequisite. Previous publications on a relevant topic is meritorious.
Documented knowledge as stated here is required.
During the assessment, emphasis will be put on your potential for research, motivation and personal suitability for the position.
Admission to the PhD programme
The position requires admission to the PhD programme at The Faculty of Engineering Science and Technology. In order to gain admission to the programme, applicants with a background from a Norwegian institution should have a weighted grade average of B or better in the Master’s degree. In cases where the candidate has received the degree from a foreign institution, admission may be granted after individual assessment. GPA (grade point average) and translation rules for the European Standardized Character System must follow the application. Applicants with a Master’s degree that does not include a Master’s thesis do not qualify for admission to the PhD programme.
More information about requirements and the PhD programme is available here: Regulations PhD Faculty of Engineering Science and Technology
Your application must include:
- Cover letter explaining your motivation and research interests
- Diplomas, diploma supplements and transcripts (master’s and bachelor’s degrees)
- Documentation of English profiency
- Contact information to 1-3 references, written references
- Master thesis, and any other academic works
The documentation has to be in English or a Scandinavian language. We only accept applications sent via www.jobbnorge.no.
- Involvement in an interesting research project
- A good academic environment with dedicated colleagues
- A large degree of independence in work
- Flexible working hours and a state collective pay agreement
- Pension scheme through the state pension fund
The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find more information for applicants.
As many as possible should have the opportunity to undertake organized research training. If you already hold a PhD or have equivalent competence, we will not appoint you to this position.
A shorter period of appointment may be decided when the PhD Fellow has already completed parts of their research training programme or when the appointment is based on a previous qualifying position PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years.
Remuneration for the position of PhD Fellow is in accordance with the State salary scale code 1017. A compulsory contribution of 2 % to the Norwegian Public Service Pension Fund will be deducted.
More practical information for working and living in Norway can be found here: http://uit.no/mobility
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background. UiT will emphasize making the necessary adaptations to the working conditions for employees with reduced functional ability.
We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). According to Offentleglova information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure. You will receive advance notification in the event of such publication, if you have requested non-disclosure.