NGI - Norwegian Geotechnical Institute

NGI – Norwegian Geotechnical Institute – is an internationally renowned center for applied research and consulting in engineering-related geosciences, integrating geotechnical, geological, and geophysical expertise. Our research provides knowledge that strengthens industry and society to solve some of the most critical challenges facing the world related to climate, environment, energy, and natural hazards.

Since the establishment of NGI in the early 1950s, we have attracted dedicated professionals and experts in using geomaterials as construction ground and building materials, landslide problems, and ground pollution. The development and application of new technology are central to our business to find sustainable solutions and ensure that we build a society on safe ground. Our expertise and solutions are known and in demand in large parts of the world.

NGI has headquarters and laboratories in Oslo, a branch office in Trondheim, an avalanche research station in Western Norway, and overseas offices in Houston, Texas, USA, and in Perth, Western Australia, as well as partnership collaboration agreements with well-established companies and institutions around the world.

As one of the charity’s main partners, NGI supports Engineers Without Borders (EWB) Norway financially and by contributing engineering expertise to its assignments for Norwegian aid organizations.

Homepage: https://www.ngi.no/en/

Doctoral Candidate position – Data assimilation for optimised design of OWT foundations.

Work description
The Norwegian Geotechnical Institute (NGI) is seeking candidates for a PhD position related to data assimilation for optimized design of Offshore Wind Turbine (OWT) foundations. For more information about NGI, see www.ngi.no. The candidate will further be enrolled in the PhD program in the Marine Technology Department at the Norwegian University of Science and Technology (NTNU) in Trondheim.

The topic for this PhD grant is related to probabilistic design for OWT foundations compatible with the observational method by incorporating uncertainties in geotechnical properties, metocean conditions and monitoring data. The position is attached to the Horizon Europe project BETTER which is a Doctoral Training Network under the Marie Skłodowska-Curie Actions (MSCA), including training of 15 individual Doctoral Candidates. The position is titled “Data assimilation for optimised design of OWT foundations” and is designated Doctoral Candidate DC11 within the project.

There are a number of important aspects, which require particular consideration in the design of OWT foundations, such as varying soil profiles and soil properties in both vertical and horizontal directions, high-cyclic loading conditions during operation, and nonlinear cyclic stress-strain behaviour of soils. OWT foundations are particularly exposed to harsh environmental conditions where both loads/actions and soil strength and stiffness are highly uncertain. To reduce the levelised-cost-of-energy by optimising the design of the required offshore infrastructure, an accurate quantification of these uncertainties under consideration of the design requirements, as well design methods that explicitly account for site-specific uncertainties, are crucial.

The doctoral candidate will be responsible for developing a novel probabilistic design procedure based on the observational method (Peck, 1969). The procedure is compatible with the general reliability framework for the observational method, by integrating the use of probability theory and observational data (i.e., data assimilation) during both installation and operational phases of a project. Implementation of such a methodology will over time lead to more efficient use of resources by avoiding unnecessary over-conservative design, and reducing the likelihood of unexpected failures, thereby improving the design of future generations of OWT foundations. This research aims to provide pathways to transform new resilience and uncertainty models into data-driven monitoring, maintenance, and design solutions.

The applicant is expected to visit partners from the BETTER consortium for secondments of about six months (or more) and will participate in joint network-wide training activities.

Pre-requisites and mandatory documents
The candidate must hold a MSc degree, or other corresponding education equivalent to a Norwegian MSc (including 120 ECTS at master’s level) covering some of the following fields: geotechnical engineering, structural engineering, marine technology, or a related field, with a demonstrated interest in offshore wind turbine foundation design and reliability analysis.

Plese read details about the mandatory documents in the following link: https://drive.google.com/file/d/1zRSrAUohnLiwO-3vu9JvkWbfyXtpkLgt/view

Grade requirements:

The candidate must satisfy the conditions for admission to the faculty’s doctoral program in Engineering at NTNU. This requires a strong academic background and an average grade from the master’s degree program, or equivalent education, which is equal to B or better compared with NTNU’s grading scale. If you do not have letter grades from previous studies, you must have an equally good academic basis. If you have a weaker grade background, you may be assessed if you can document that you are particularly suitable for a PhD education.

Competence Requirements

In addition to the formal requirements listed above, applicants must possess strong programming skills (e.g. Fortran) and scripting proficiency (e.g. Python). Moreover, experience in one or more of the following topics will be highly valued:

Advanced numerical modelling techniques, such as finite element analysis (FEA).
Background in statistics, probability theory, and machine learning. Offshore wind projects or offshore wind turbine foundation design.

We look for enthusiastic persons which like to work and study with other young researchers and with a particular interest to international relationships.

Additional information
The salary consists of the gross Monthly Living Allowance of 3.400,00 EUR per month pondered by the EU correction coefficient (specific for the countries where the enrolling Institutions are located, available at link); in addition, a Mobility Allowance of 600,00 EUR per month will be paid, and also possibly another 495,00 EUR per month of Family Allowance depending on marital status.

The DC salary is subject to local tax, social benefit and other deductions following national regulations.

Eligibility criteria

The PhD position as Doctoral Candidates is open to applicants of all nationalities fulfilling with the following eligibility requirements:

should have — at the date of recruitment — LESS than 4 years of a research career and not have a doctoral degree. The 4 years are measured from the date when the applicant obtained the degree which would formally entitle him/her to embark on a PhD, either in the country where the degree was obtained or in the country where the PhD is provided.
should NOT have — at the date of recruitment — resided in the country where the research training takes place for more than 12 months in the 3 years immediately prior to recruitment, and NOT have carried out his/her main activity (work, studies, etc.) in that country.
should satisfy the eligibility requirements to enrol on a PhD degree. This includes i) master degree compliant with the research fields described in the individual research project; ii) excellent/good oral and written English language skills, iii) good skills in scientific writing and results presentation.

Selection process
Interested students are asked to submit their application within August 20th, 2025.
A recruitment panel adhering to strict gender equality and equal opportunity rules will be set up consisting of the two supervisors and a third BETTER representative.
After a first evaluation based on the provided documents, an online interview will follow.
Selection criteria will encompass the potential as researchers, creativity, level of independence, teamwork ability, knowledge, communication experience and availability for the intended start date. Start date of the positions can be earlier, but all positions must be filled by November 2025.

Please submit your application by Aug 20th, 2025 by using following link: https://candidate.hr-manager.net/ApplicationInit.aspx?cid=388&ProjectId=175851&DepartmentId=17357&MediaId=4181