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Jan Sandstad Næss

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PhD Candidate in Societal Readiness for AI-supported Life Cycle Assessment of Buildings Norwegian University of Science and Technology in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Nov 17, 2026

Country flag

Country

Norway

University

Norwegian Institute of Science and Technology

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Keywords

Computer Science
Environmental Science
Sociology
Artificial Intelligence
Civil Engineering
Science And Technology Studies
Architecture
Construction Management
Life Cycle Assessment
Environmental Governance
Decision Support System
Large Language Models
ML

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About this position

NTNU (Norwegian University of Science and Technology) is offering a 3-year PhD position in Societal readiness for AI-supported Life Cycle Assessment of buildings at the Department of Architecture and Technology in Trondheim, Norway.

The project sits within the Energy and Environment Group, a multidisciplinary research environment connected to major initiatives such as the Research centre on zero emission neighbourhoods in smart cities (ZEN), syn.ikia – Sustainable plus energy neighbourhoods, and the Green Deal ARV project on Climate positive circular communities. The group also makes use of real demonstration projects and NTNU’s laboratory facilities, including the ZEB laboratory. The position will be carried out in cooperation with SINTEF Industry and NTNU Social Research.

The research focuses on how artificial intelligence is changing life cycle assessment (LCA) practice in the architecture, engineering, and construction sectors. AI-supported tools can automate data gathering, model construction, scenario generation, result interpretation, and decision support. While these tools may improve speed and usability, especially in early design stages, they also raise questions about transparency, methodological integrity, accountability, professional judgement, and institutional preparedness.

The PhD project will investigate the societal readiness of the sector for AI-supported environmental assessments using a mixed-method approach and case applications. The project specifically mentions machine-learning approaches, large language models, and automated workflows. It aims to understand how these tools reshape trust, responsibility, accountability, and professional judgement in environmental decision-making.

Applicants must qualify for admission to the doctoral programme in architecture and hold a relevant master’s degree in Architecture, Industrial Ecology, Science and Technology Studies, Computer Science, or an equivalent field. The degree must include a major independent project of at least 30 ECTS. A strong academic record is expected, including an average grade of B or better on the NTNU scale, with possible flexibility for candidates who can demonstrate exceptional suitability through relevant work experience or peer-reviewed work. Excellent English skills are required, and experience with LCA, AI, programming, or Science and Technology Studies concepts is preferred. Norwegian or Scandinavian language skills are seen positively.

The position requires 30 ECTS of academic coursework during the PhD, participation in international activities such as conferences or research stays, and publication in high-quality peer-reviewed journals. The successful candidate may also be offered career-enhancing tasks such as teaching, supervision, laboratory work, or examination duties if the department needs this and the candidate is motivated and capable.

Employment is for 3 years and the gross salary normally starts at NOK 580,000 per annum, with standard public pension contributions. The application deadline is 2026-11-17. Applications must be submitted electronically via Jobbnorge.no.

Required application documents include transcripts and diplomas for bachelor’s and master’s degrees, a CV, a copy or draft of the master’s thesis, a short motivation letter, a 1-2 page sketch describing the fit between background and research ambitions, a list of publications or other research work if relevant, any supporting certificates, and contact information for three referees. Applicants with education from outside Norway should also provide documentation of the scope and quality of their education, including a diploma supplement or HK-dir statement if available.

Funding details

Available

What's required

Applicants must meet admission requirements for the doctoral program in architecture and hold a relevant Master's degree in Architecture, Industrial Ecology, Science and Technology Studies, Computer Science, or equivalent. The degree must include a major independent project of at least 30 ECTS equivalent to a master's thesis. Master students may apply, but the degree must be completed and documented before starting and no later than 2026-11-01. Applicants should have a strong relevant academic background with an average grade of B or better on NTNU's scale, or an equally strong academic foundation if grades are not available. Candidates with weaker grades may still be considered if exceptionally suited for PhD education through relevant work experience and/or peer-reviewed publications. Excellent written and oral English skills are required, along with strong analytical skills and motivation for the topic. Preferred qualifications include competence in Life Cycle Assessment or other environmental sustainability analysis methods, experience with AI tools such as large language models or machine learning, good programming skills (e.g., Python, MATLAB, R), familiarity with Science and Technology Studies concepts such as co-production, and good oral and written presentation skills in Norwegian or Scandinavian languages.

How to apply

Apply electronically via Jobbnorge.no before the deadline. Include transcripts and diplomas for bachelor's and master's degrees, CV, master's thesis or draft, a short motivation letter, a 1-2 page research sketch, publication list if applicable, other relevant certificates, and names/contact information for three referees. If educated abroad, also attach documentation of degree scope and quality and diploma supplement or HK-dir statement if available.

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Professors

Associate Professor at Norwegian University of Science and Technology

University Name
Country flag

Norway

Research Interests

Artificial Intelligence

Construction Management

Environmental Governance

Civil Engineering

Ml