PhD position within Spatial Mobility Analytics

Deadline: 18.02.2022

Norwegian University of Life Sciences

NMBU has a particular responsibility for research and education that secures the basis for the life of future generations. Sustainability is rooted in everything we do and we deliver knowledge for life. NMBU has 1,900 employees of which about 300 phd scholarships and 6,700 students. The university is divided into seven faculties.

NMBU believes that a good working environment is characterised by diversity.

We encourage qualified candidates to apply regardless of gender, functional ability, cultural background or whether you have been outside the labour market for a period. If necessary, workplace adaptations will be made for persons with disabilities.

More information about NMBU is available at www.nmbu.no.

About The Faculty of Science and Technology

The Faculty of Science and Technology (REALTEK) develops research-based knowledge and educates civil engineers and lecturers needed to reach the UN's sustainability goals. We have approximately 150 employees, 70 PhD students and soon 1500 students. The education and research at REALTEK cover a broad spectrum of disciplines.

This includes data science, mechanics and process engineering, robotics, construction and architecture, industrial economics, environmental physics and renewable energy, geomatics, water and environmental engineering, applied mathematics as well as secondary school teacher education in natural sciences and use of natural resources such as in agriculture, forestry and aquaculture. The workplace is in Ås, 30 km from Oslo.

We are looking for a highly motivated researcher with a passion for GIScience and as well as a strong research interest in Movement Data Science.

About the position

The Faculty of Science and Technology at the Norwegian University of Life Sciences (NMBU) has a vacant PhD–position related to spatial mobility analytics. The PhD position is for a period of 3 years, or up to 4 years if teaching and other work duties are agreed.

Responding and adapting to the new reality after the COVID-19 pandemic, we need new urban intelligent and planning that create resilient and sustainable cities and communities (ref. Sustainable Development Goal 11). The aim of the proposed PhD project is to use heterogeneous data sets and technology to observe (changes in) mobility patterns of people before and after the COVID-19 pandemic.

It is expected that the traditional homework commuting flow will give its place to new mobility patterns given huge shift towards remote-working culture. This major transformation in mobility within the urban ecosystem needs to be fully studied to not only support planning authorities with their promoted plan proposals but individuals with their commuting decisions.

Main tasks

The main activities will be linked to the following:

  • Developing data analytics, machine learning and knowledge discovery methods to advance the knowledge and understanding of how mobility patterns are formed and evolved in an urban dynamic system integrating heterogeneous data sets.
  • Analyzing costs and benefits of urban mobility changes across various spatial and temporal scales (e.g., possible disparities in mobility from neighborhoods to cities and regions and in pre / post COVID-19 pandemic periods).
  • Visualizing the findings with innovative methods to enhance fundamental knowledge on changes in mobility patterns in space and time and across scales.
  • Proposing intelligent human-centered urban mobility plans incorporating different qualitative/quantitative scenario-based approaches.

The successful candidate is expected to enter a plan for the progress of the work towards a PhD degree during the first months of the appointment, with a view to completing a doctorate within the PhD scholarship period.


In order to be appointed, the candidate must meet the requirements for admission to one of the PhD programs at NMBU. A master's degree of at least 120 credits (ECTS) is required, which is based on a bachelor's degree of at least 180 credits (ECTS), or cand.med.vet. degree, or integrated master's degree of at least 300 credits (ECTS). The applicant must have a documented strong academic background from previous studies, and be able to document good English skills, both written and oral. For more detailed information on admission criteria, see the PhD Regulations and the “supplementary provisions for the PhD programmes”.

The applicant must document expertise and interest in the research subject.

Required Academic qualifications

  • Master’s degree within Geomatics, GIScience, Computer Science, Data Science, or a related field.

The following experiences and skills will be emphasized:

  • Strong background in quantitative data analysis, computational modelling, and spatial-temporal data analysis
  • Practical experience in big data fusion and processing
  • Practical experience in machine/deep learning
  • Programming language (e.g., Python, R, JavaScript)

You need:

  • Strong motivation and commitment.
  • Curiosity and high motivation for research.
  • Ability to work hard and independently.
  • Profound interest in collaborating in an interdisciplinary research team.
  • Strong communication skills, both written and oral English.

Practical experience within the mentioned required academic qualifications is required. We expect that the candidate will successfully publish research findings in high-impact peer reviewed journals.

Remuneration and further information

The PhD position is placed in government pay scale position code 1017.

PhD fellows are normally placed in pay grade 54 (NOK 491.200,-) on the Norwegian Government salary scale upon employment and follow ordinary meriting regulations.

Terms of employment are governed by Norwegian guidelines for PhD fellowships at Universities and University Colleges.

For further information, please contact:

Information for PhD applicants and general Information to applicants.


To apply online for this vacancy, please click on the 'Apply for this job' button above. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.

Application deadline: 18.02.2022

Publications should be included electronically within the application deadline. Printed material which cannot be sent electronically should be sent by surface mail to the Norwegian University of Life Sciences, Faculty of Science and Technology, P.O. Box 5003, NO-1432 Ås, within 18.02.2022. Please quote reference number 21/06267

If it is difficult to judge the applicant’s contribution for publications with multiple authors, a short description of the applicant’s contribution must be included.

Applications should include (electronically):

  • A letter of intent
  • Curriculum vitae
  • Full publication list
  • Copies of degree certificates and transcripts of academic records (all certified)
  • A list of two persons who may act as references (with phone numbers and e-mail addresses)
  • Proof of English proficiency must be attached in accordance with NMBU PhD regulation section 5-2 (3).

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