PhD position in Climate-Resilient Stormwater Management with Data-Driven and Nature-Based Solutions

Arbeidsplassen; Ås; On-site; NOK 551,000; Full time

Job summary

A PhD position focusing on Climate-Resilient Stormwater Management is available at NMBU. This role emphasizes data-driven and nature-based solutions, aiming to develop adaptive strategies for urban flooding and stormwater management in response to climate change. Ideal candidates will possess a master's degree in relevant fields and strong skills in machine learning and hydraulic modeling.

Qualifications

• Master's degree or equivalent in relevant fields required.
• Proficiency in English, Norwegian preferred.
• Solid understanding of hydrology and stormwater management.

Responsibilities

• Conduct a literature review on stormwater management.
• Analyze rainfall scenarios and develop machine learning models.
• Collaborate with stakeholders across Norway.

Skills

Machine Learning

Data Analysis

Hydraulic Modeling

Optimization Techniques

Environmental Modeling

Education

Master's degree in Civil Engineering

Equivalent in Water Engineering or Environmental Engineering

Tools

SWMM

GIS

Python

R

MATLAB

Job description

PhD position in Climate-Resilient Stormwater Management with Data-Driven and Nature-Based Solutions

PhD Climate-Resilient Stormwater Management with Data-Driven and Nature-Based Solutions - 25/02983

• The PhD position is for a period of 3 years.

Urban stormwater systems are increasingly under pressure from climate change, urban densification, and aging infrastructure. Conventional drainage networks are not designed to cope with the frequency and intensity of extreme weather events predicted under future climate scenarios, leading to growing risks of urban flooding, water pollution, and infrastructure damage. This is a particularly urgent concern in Nordic countries such as Norway, where climate projections indicate more intense rainfall and wetter conditions in many cities. There is a pressing need to develop adaptive, robust, and resilient solutions for stormwater management that leverage modern technologies and sustainable practices.

This PhD position offers a unique opportunity to advance urban stormwater engineering through data-driven and nature-based approaches, including Low Impact Development (LID) practices (e.g., green roofs, rain gardens), with a specific focus on urban catchments. The research will place a strong emphasis on machine learning, optimization techniques, and climate change scenario analysis. The successful candidate will contribute to the development of intelligent models and decision-support tools that enhance the performance, resilience, and sustainability of stormwater management.

The research will focus on integrating AI and machine learning with hydraulic-hydrologic modeling, urban planning strategies, and nature-based infrastructure to better predict and manage stormwater dynamics under climate-related uncertainty. It will also explore how to optimize design and operation strategies to adapt to future climate extremes.

Possible areas of research include:

• Developing machine learning models as surrogate models for predicting flooding and stormwater system responses under various nature-based solution (NBS) configurations and climate scenarios.
• Using hydrologic and hydraulic simulations to generate training data and assess stormwater system performance under future climate conditions.
• Designing and applying multi-objective optimization techniques to explore trade-offs among flood risk reduction, environmental co-benefits, cost-efficiency, and land use.
• Assessing the resilience and adaptability of nature-based (blue-green) and hybrid (gray-green) stormwater solutions.
• Integrating uncertainty analysis and multi-criteria decision-making to support long-term planning and scenario evaluation.
• Collaborating with utilities to apply and validate the developed models using real-world case studies and data.

The research plan will be tailored based on the candidate’s background in flood management, data science, environmental modeling, and systems optimization. The candidate will work actively as part of theWater Transport Systems and Stormwater Management research group . This position offers the opportunity to advance innovative, data-driven, and nature-based stormwater management strategies that enhance urban resilience, reduce flood risks, and promote sustainable adaptation to climate change in Nordic cities.

The successful candidate will also have access to the faculty’s advanced resources in water and environmental engineering, as well as expertise in artificial intelligence. In addition, they may benefit from the Department of Data Science at REALTEK, which offers a broader community in machine learning.

You will join the research efforts at the Department of Building and Environmental Technology at NMBU and contribute to its development. As a student in thePhD Programme Science and Technology , you will work towards your doctoral thesis and earn your PhD upon successful defense of your thesis.

Description of tasks or PhD project:

• Conduct a comprehensive literature review on data-driven and nature-based stormwater management.
• Analyze extreme rainfall scenarios using downscaled climate projections under recent emissions pathways (e.g., SSP-RCP scenarios), combined with observed runoff and flood data.
• Develop machine learning models to predict urban flooding and stormwater responses under climate change conditions.
• Integrate hydraulic-hydrologic modeling and surrogate models (e.g., Bayesian Networks) to simulate stormwater behavior under future scenarios.
• Apply optimization techniques to design and evaluate nature-based and hybrid stormwater solutions.
• Assess resilience and co-benefits of smart, sustainable stormwater strategies.
• Collaborate with stakeholders and utilities in Norway to apply methods in real-world case studies.
• Publish findings in high-quality peer-reviewed journals and present at conferences.

Competence

About the position

A PhD position in Climate-Resilient Urban Stormwater Management with Data-Driven and Nature-Based Solutions is available at theDepartment of Building and Environmental Technology at theFaculty of Science and Technology .

• The PhD position is for a period of 3 years.
• Desired start date: 1. November 2025

Urban stormwater systems are increasingly under pressure from climate change, urban densification, and aging infrastructure. Conventional drainage networks are not designed to cope with the frequency and intensity of extreme weather events predicted under future climate scenarios, leading to growing risks of urban flooding, water pollution, and infrastructure damage. This is a particularly urgent concern in Nordic countries such as Norway, where climate projections indicate more intense rainfall and wetter conditions in many cities. There is a pressing need to develop adaptive, robust, and resilient solutions for stormwater management that leverage modern technologies and sustainable practices.

This PhD position offers a unique opportunity to advance urban stormwater engineering through data-driven and nature-based approaches, including Low Impact Development (LID) practices (e.g., green roofs, rain gardens), with a specific focus on urban catchments. The research will place a strong emphasis on machine learning, optimization techniques, and climate change scenario analysis. The successful candidate will contribute to the development of intelligent models and decision-support tools that enhance the performance, resilience, and sustainability of stormwater management.

The research will focus on integrating AI and machine learning with hydraulic-hydrologic modeling, urban planning strategies, and nature-based infrastructure to better predict and manage stormwater dynamics under climate-related uncertainty. It will also explore how to optimize design and operation strategies to adapt to future climate extremes.

Possible areas of research include:

• Developing machine learning models as surrogate models for predicting flooding and stormwater system responses under various nature-based solution (NBS) configurations and climate scenarios.
• Using hydrologic and hydraulic simulations to generate training data and assess stormwater system performance under future climate conditions.
• Designing and applying multi-objective optimization techniques to explore trade-offs among flood risk reduction, environmental co-benefits, cost-efficiency, and land use.
• Assessing the resilience and adaptability of nature-based (blue-green) and hybrid (gray-green) stormwater solutions.
• Integrating uncertainty analysis and multi-criteria decision-making to support long-term planning and scenario evaluation.
• Collaborating with utilities to apply and validate the developed models using real-world case studies and data.

The research plan will be tailored based on the candidate’s background in flood management, data science, environmental modeling, and systems optimization. The candidate will work actively as part of theWater Transport Systems and Stormwater Management research group . This position offers the opportunity to advance innovative, data-driven, and nature-based stormwater management strategies that enhance urban resilience, reduce flood risks, and promote sustainable adaptation to climate change in Nordic cities.

The successful candidate will also have access to the faculty’s advanced resources in water and environmental engineering, as well as expertise in artificial intelligence. In addition, they may benefit from the Department of Data Science at REALTEK, which offers a broader community in machine learning.

You will join the research efforts at the Department of Building and Environmental Technology at NMBU and contribute to its development. As a student in thePhD Programme Science and Technology , you will work towards your doctoral thesis and earn your PhD upon successful defense of your thesis.

Main tasks

Description of tasks or PhD project:

• Conduct a comprehensive literature review on data-driven and nature-based stormwater management.
• Analyze extreme rainfall scenarios using downscaled climate projections under recent emissions pathways (e.g., SSP-RCP scenarios), combined with observed runoff and flood data.
• Develop machine learning models to predict urban flooding and stormwater responses under climate change conditions.
• Integrate hydraulic-hydrologic modeling and surrogate models (e.g., Bayesian Networks) to simulate stormwater behavior under future scenarios.
• Apply optimization techniques to design and evaluate nature-based and hybrid stormwater solutions.
• Assess resilience and co-benefits of smart, sustainable stormwater strategies.
• Collaborate with stakeholders and utilities in Norway to apply methods in real-world case studies.
• Publish findings in high-quality peer-reviewed journals and present at conferences.

Competence

Required qualifications

• A Master's degree or equivalent in Civil Engineering, Water Engineering, Hydrology, Wastewater/Environmental Engineering, or a closely related field. Foreigndegrees must correspond with theadmission criteria for the PhD program. Candidates who submit their MSc thesis by the application deadline may be considered.
• Proficiency in both written and oral English in correspondence with theadmission criteria for the PhD program.
• Personal suitability and motivation for the position.

The following experiences and skills will be emphasized:

• Solid understanding of urban hydrology, stormwater management, and climate adaptation strategies — familiarity with Nordic climate and hydrological conditions is an advantage
• Experience with machine learning models and hydrologic/hydraulic modeling
• Strong familiarity with tools such as SWMM and GIS
• Proficiency in programming and data analysis (e.g., Python, R, MATLAB)
• Background or interest in nature-based solutions and optimization techniques
• Experience in working with climate model outputs and scenario analysis is an advantage
• A proven record of scientific writing and publications in peer-reviewed journals is an advantage

Applicants who have recently graduated with excellent results may be given preference.

Personal qualities:

• Ability to work independently and motivated to collaborate in an interdisciplinary team
• Strong communication skills (English required; Norwegian is considered an advantage)
• Excellent social and collaborative skills
• Strong problem-solving abilities and a proactive approach to research challenges

The successful applicantmust meet the conditions defined for admission to a PhD programme at NMBU. For more detailed information on the admission criteria please see thePhD Regulations and the relevantPhD programmedescription .

Remuneration and further information

We offer:

• Salary 550 800 NOK per annum. For exceptionally well qualified candidates a higher salary may be considered.
• Government pay scale position code 1017 PhD Research Fellow.

Formal regulations

The appointment is to be made in accordance withRegulations on terms of employment for positions such as postdoctoral fellow, Phd candidate, research assistant and specialist candidate and Regulations concerning the degrees of Philosophiae Doctor (PhD) at the Norwegian University of Life Science (NMBU)

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Norwegian Security and Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter laws will be prohibited from recruitment.

For further information, please contact Dr. Abbas Roozbahani, Associate Professor, E-mail:[e-mail] (do not use this e-mail for application, it is only for questions)

Information for PhD applicants and generalinformation to applicants

Application

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: 11.08.2025

Please note that all documents should be in English or a Scandinavian language.

By applying the candidate confirms that information and documentation submitted via the job application can also be used by NMBU in a possible admission process to the PhD program.

Interviews with the best qualified candidates will be arranged.Applicants invited for an interview are expected to present original diplomas and certificates.

The application must include:

• Motivation letter (maximum 1 page)
• Curriculum Vitae (with a list of education, positions, teaching experience, administrative experience and other qualifying activities, including a complete list of publications)
• Certified copies of academic diplomas and certificates. (i.e. Di-ploma, transcript. Diploma supplement for both bachelor and master). Diplomas, transcripts and diploma supplements that are not in Norwegian or English must be uploaded in the original language. An English translation of these documents must also be attached.
• Applicants from universities outside Norway are kindly requested to send a diploma supplement, or a similar document, which describes in detail the study program and grading system.
• Documentation of proficiency in written and oral English in accordance withNMBU PhD regulationsection 5-2 (3) .
• Names and contact details for two references
• Additional relevant documentation of professional knowledge (for example, list of scientific works).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.

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.

What is it really like to work at the Faculty of Science and Technology (REALTEK) at NMBU?

- Guided tour of the Faculty of Science and Technology on Vimeo

NMBU will contribute to securing the future of life through outstanding research, education, communication and innovation. We have the country's most satisfied university students, who receive research-based education in a unique student environment. Our graduates gain a high level of competence in interdisciplinary collaboration and are popular in the labor market.

NMBU has internationally leading research environments in several subjects. Together with our partners in society and business, we contribute to solving some of the biggest societal challenges of our time. We focus on innovation, communication and entrepreneurship because we believe these challenges are best solved with joint efforts. We believe that a good working environment is characterized by diversity.If necessary, workplace adaptations will be made for persons with disabilities. More information about NMBU is available at www.nmbu.no/en