Ledig stilling ved UiT Norges arktiske universitet

PhD Fellow in Machine Learning in Continuum Materials Mechanics

Deadline: 10.02.2020

The position

The Faculty of Engineering Science and Technology, Department of building, energy and material technology has a PhD position vacant for applicants who wish to obtain the degree of Philosophy Doctor (PhD). The position is attached to the research group Building, energy and material technology (BEaM). The position is at UiT the Arctic University of Norway in Narvik.

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.

The appointment is for a period of four years.

The PhD position is for a fixed term, with the objective of completion of 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 in plasticity and fracture characterization and modelling in metals. The traditional approach to characterization and modelling of plastic deformation and fracture in metals is based on constitutive equations, which may be phenomenological or derived from some physical principles. When these equations are used to predict the behavior of the material undergoing complex stress-strain history, the results are often not very accurate.

The artificial neural networks (ANN) is an alternative method of material modelling, which may provide more accurate predictions. The accurate predictions of the plasticity and fracture in metals is important in optimizing both the production and service life of various structural components, which may lead to reduced waste and saving raw materials and energy. This PhD will investigate the numerical aspects of using ANN in the context of finite element modelling of metals as well as the experimental approaches that may suit the ANN better than the traditional mechanical tests.

The position’s affiliation

The positions will be affiliated with the department of building, energy and material technology, and the PhD fellow will be part of the research group Building, energy and material technology (BEaM). The department is responsible for various study programs related to building technology, as well as to renewable energy, and the number of students are approximately 400.

The department organizes most research activities under research groups. The group conducts applied research in interdisciplinary themes of building, energy and material to develop technologies that are energy efficient, environmentally friendly and sustainable. Our research strengths are in construction technologies and renovation of buildings, renewable energy technologies including bio energy, hydrogen and fuel cells and building materials especially for cold climate and the Arctic conditions.

Contact

Further information about the position available by contacting:

Qualifications

The candidate should have bachelor degree in Material, Mechanical or Structural engineering and masters engineering in the field relevant to the theme of the projects. The applicant may present a description outlining the academic basis of the PhD project.

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 applicant 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.

The applicant must also be able to document proficiency in Scandinavian or English equivalent to Norwegian Higher Education Entrance Qualification, refer to the website about applying for a PhD position. Information about the application process for admission to the PhD programme, application form and regulations for the degree of Philosophiae Doctor (PhD) is available here.

During the assessment emphasis will be put on your potential for research, motivation and personal suitability for the position.

Application

Your application must include:

  • Cover letter explaining your motivation and research interests
  • CV (containing a complete overview of education, supervised professional training and professional work)
  • Proposal for project description
  • Diplomas and transcripts from completed degrees
    • diploma and transcript from your Bachelor’s degree or equivalent
    • diploma and transcript from your Master’s degree or equivalent
    • diploma supplement for completed degrees
  • Documentation of English language proficiency
  • List of references with contact information
  • Master thesis, and any other academic works

Documentation has to be in English or a Scandinavian language. We only accept applications through Jobbnorge.

Assessment

The applicants will be assessed by an expert committee. During this assessment process, emphasis will be attached to the applicant’s potential for research as shown by the application.

Consideration may be given to work experience or other activities of significance for the implementation of the PhD studies, and to any teaching qualifications. Information and material to be considered during the assessment must be submitted by the stipulated deadline.

The applicants who are assessed as the best qualified will called to an interview. The interview shall among other things aim to clarify the applicant’s personal suitability for the position.

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.

Working conditions

The appointment is for a period of 4 years, and the nominal length of the PhD program is three years. The fourth year is distributed as 25 % of each year, and will consist of teaching or other duties for the department.

A shorter period of appointment may be decided when the research fellow has already completed parts of his/her research training programme or when the appointment is based on a previous qualifying position (PhD Candidate, 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 Candidate 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!

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.

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.

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