PhD Position in Graph Neural Networks Modelling
About the position
This PhD position is a part of NTNUs initiative to establish a Center for Green Shift in the Built Environment hosted by the department of Civil and Environmental Engineering. The Center’s vision is to create value in the society through Digitalisation. This center will utilize and develop expertise, methods, tools and strategies for a sustainable built environment. The research and innovation activities of the center will be directed at a Green Shift and a Digital Future.
The PhD candidate will be part of the Water and Wastewater Engineering group at NTNU (https://www.ntnu.edu/ibm/water-and-wastewater-engineering). This position is a fixed term, full time (100 %) position for 3 years. The candidate will cooperate internationally with TU Delft AI Lab for sustainable water management (AidroLab, https://www.tudelft.nl/en/ai/ai-labs/aidrolab/) and TU Graz Institute of Highway Engineering and Transport Planning (https://www.tugraz.at/en/institutes/isv).
The PhD candidate will report to his or her main supervisor.
Duties of the position
Thesis Topic: Interpretable Models with Graph Neural Networks to support the Green Transition of Critical Infrastructures
Climate change challenges our current infrastructure to become more resilient and efficient within the next decade(s). The digital revolution opens up ample opportunities to support this green transition by providing us with a massive amount of data. Artificial Intelligence (AI) algorithms are taking leverage of these new data resources and provide new technologies to increase the resilience and efficiency of our systems tremendously. Since all infrastructure networks can be described mathematically as graphs, recent advancements in Graph Neural Networks (GNNs) lay the foundation for more sophisticated, interpretable and flexible reasoning within machine learning for critical infrastructures such as water, wastewater, and transportation networks.
The PhD candidate will work on a challenging problem at the interface between machine learning and civil engineering. The aim of the thesis is to develop data-driven models of critical infrastructure networks based on GNNs. These models will support infrastructure planners in (i) identifying which parts are most vulnerable to climate change, (ii) revealing where most efficiency is lost, and (iii) suggesting structural alternatives to circumvent systematic flaws with respect to the coming green transition. Furthermore, the PhD will compare the applicability of GNNs in two inherently different areas: (i) urban water systems vs. (ii) transportation networks.
- Develop a research plan for the PhD dissertation and conduct research accordingly
- Get actively involved in the Center for Green Shift in the Built Environment
- Participate in research at the Water and Wastewater Engineering group
- Write scientific publications (journals papers, conferences abstracts)
- Attend and present at conferences, workshops and networking events in Norway and abroad
- Comply with the PhD training program of the Faculty
Required selection criteria
The PhD-position's main objective is to qualify for work in research positions. The qualification requirement is that you have completed a master’s degree or second degree (equivalent to 120 credits) with a strong academic background in Civil Engineering, Computer Science, Control Engineering, Physics, Applied Mathematics or equivalent education with a grade of B or better in terms of NTNU’s grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you are unable to meet these criteria you may be considered only if you can document that you are particularly suitable for education leading to a PhD degree.
The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and national guidelines for appointment as PhD, post doctor and research assistant.
- Proficient in Programming (Python, R, Matlab or similar scientific computing environments)
- Good English skills (written and oral)
Preferred selection criteria
- Knowledge and experience within machine learning and AI are preferred and should be highlighted, especially experience with respect to neural networks and deep learning, including programming environments (e.g. Keras, TensorFlow, pyTorch, …)
- A strong mathematical background, especially in Linear Algebra and Network theory, is advantageous
- Knowledge on statistics, uncertainty quantification and data analysis are an additional asset
- Experience with infrastructure networks, especially urban water and/or transport, but also with similar infrastructures like telecommunication networks or electrical grids is an advantage
- Knowledge and experience with hydraulic modelling (e.g. EPANET, SWMM, …) counts as an additional advantage
The ideal candidate
- Is scientifically curious and open to new research challenges with an affinity for AI
- Enjoys working in a multi-disciplinary project and international team
- Demonstrates independence and persistence in addressing technical problems
- Is flexible and reliable, with ability to work effectively independently and as part of a team
- exciting and stimulating tasks in a strong international academic environment
- an open and inclusive work environment with dedicated colleagues
- favourable terms in the Norwegian Public Service Pension Fund
- employee benefits
Salary and conditions
PhD candidates are remunerated in code 1017, and are normally remunerated at gross from NOK 482 200 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is 3 years.
Appointment to a PhD position requires that you are admitted to the PhD programme in Engineering (https://www.ntnu.edu/studies/phiv) within three months of employment, and that you participate in an organized PhD programme during the employment period
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to 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 law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.
It is a prerequisite you can be present at and accessible to the institution daily.
About the application
The application and supporting documentation to be used as the basis for the assessment must be in English.
Publications and other scientific work must follow the application. Please note that applications are only evaluated based on the information available on the application deadline. You should ensure that your application shows clearly how your skills and experience meet the criteria which are set out above.
The application must include:
- Motivation letter: A short letter (0.5-2 pages) showing the applicant’s motivation for a PhD study, her/his understanding and thoughts of the research topic of the position, and indicating how the applicant envisages her/his contribution within the project
- CV which includes information about education background, work experience, and information which is relevant for the position
- Certified copies of academic diplomas and transcripts (in English, German, or Norwegian)
- Language test certificates, if available (e.g. TOEFL, IELTS, and Cambridge Certificate)
- Contact information for at least 3 reference persons
Publications and other academic works that the applicant would like to be considered in the evaluation must accompany the application. Joint works will be considered. If it is difficult to identify the individual applicant's contribution to joint works, the applicant must include a brief description of his or her contribution.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.
Information Act (Offentleglova), your name, age, position and municipality may be made public even if you have requested not to have your name entered on the list of applicants.
If you have any questions about the position, please contact David Steffelbauer, telephone
+47 95186817, email firstname.lastname@example.org. If you have any questions about the recruitment process, please contact Hege Johansen, e-mail: email@example.com
Please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates. Applications submitted elsewhere will not be considered. Diploma Supplement is required to attach for European Master Diplomas outside Norway. Chinese applicants are required to provide confirmation of Master Diploma from China Credentials Verification (CHSI).
If you are invited for interview you must include certified copies of transcripts and reference letters. Please refer to the application number SO-IV 15/21 when applying.
Application deadline: 01.02.21
NTNU - knowledge for a better world
The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.
Department of Civil and Environmental Engineering
We conduct research and teaching in civil and transportation engineering, technical planning, structural engineering, water and wastewater engineering and hydraulic engineering. Graduates from our programmes become employees – in both the public and private sectors – with a sustainability mindset combined with competitive knowledge and skills. The Department of Civil and Environmental Engineering is one of eight departments in the Faculty of Engineering.
Deadline 1st February 2021
Employer NTNU - Norwegian University of Science and Technology
Place of service Vassbygget