Ledig stilling ved UiT Norges arktiske universitet
Three PhD Fellows in Applied Mathematics, Computational Engineering and Artificial Intelligence
Deadline: 11.11.2020
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 position
The Faculty of Engineering Science and Technology, Department of Computer Science and Computational Engineering has three PhD positions vacant for applicants who wish to obtain the degree of Philosophy Doctor (PhD). The positions are attached to the research groups Simulations and Artificial Intelligence.
The workplace is at UiT in Narvik. The candidate must be able to start in the position within a reasonable time, within 6 months after receiving the offer.Each position is for a fixed term 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 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.
Fields of research
The fields of research for two of the positions are applied and computational mathematics, geometric modelling, application of finite element methods in modelling, multivariate analysis, computational geometry. and additive production. The positions combined cover a wide range of research methods spanning from numerical simulations and practical experiments to development of new methods and algorithms. The scope of the work is application of spline methods for geometric modelling in additive manufacturing technology, representation of 3D model data and analysis-based design. Traditionally, spline-based techniques are used for modelling and simulations white 3D models for printing are represented as triangulations. The limitations in interoperability makes the analysis-based design hard for implementation and manufacturing.
One key activity is related to assembling a tool for analysis-based design applied to additive manufacturing. The proposed framework includes methods that utilize the same tool for modelling, simulations and additive manufacturing, and the development of algorithms for structural improvement of 3D models for additive manufacturing.
Another key activity is numerical control of 3D printers of various kinds, including exploitation of multi-materials and self-support structures. One goal is to identify limitations of standard additive manufacturing technologies with respect to 3D model representations, geometry and topology. This activity is expected to be in a strong connection with the first one, as the research is experimental based and intended to provide data for the numerical analysis and further confirmation of the new methods.
The third position' s field of research is application of machine learning methods in analysis, composition, modelling or guidance of model design. One problem with including machine learning methods in the process is the loss of transparency, combined with challenges in mathematical analysis to ensure numerical stability. Synthetic compositions for both audio and visual purposes could be obtained by augmenting traditional analysis and design techniques with machine learning. Machine learning methods can be used as a support tool in a global analysis-based design framework or used to generate synthetic composition of music. Preliminary steps for the synthetic composition include categorization, pattern recognition, and input preparation.
The purpose of these PhD projects is to investigate methods for mathematical modelling and analysis of additive manufacturing in spline frameworks, and to develop algorithms for guidance and control by combining principles of analysis-based design with numerical control, augmented with machine learning.
Affiliation
The positions will be affiliated with the Department of Computer Science and Computational Engineering, and the PhD fellows will be part of the research groups Simulations and/or Artificial Intelligence. 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 of its research activities under research groups by conducting fundamental and applied research in topics such as geometric modelling, numerical simulations, programming and visualization, artificial intelligence, machine learning and related areas.
Contact
Further information about the positions is available by contacting:
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 some of the following fields are desirable:
algorithms and programming
numerical methods
computational geometry
spline theory
finite element analysis
machine learning
artificial intelligence and intelligent agents
CAD/CAM software
Technical skills in C/C++, Matlab, Python and GMLib are beneficial. Previous publications on a relevant topic is meritorious.
Qualification with a Master’s degree is required before commencement in the position. If you are near completion of your Master’s degree, you may still apply and submit a draft version of the thesis and a statement from your supervisor or institution indicating when the degree will be obtained. You must document completion of your degree before commencement in the position.
Documented fluency in English 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.
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.
We offer
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
General information
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: Welcome to UiT!
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.
