"Postdoc Researcher in Probabilistic Surrogate Modelling for Floating Solar Farms"

Job description

Join the DigiOcean4Solar project to develop a Digital Ocean environment for fast and reliable simulations of wind-wave-structure interactions in floating solar farms.

We are looking for a highly motivated and talented Postdoctoral Researcher to join the DigiOcean4Solar project. Offshore floating solar is a rapidly emerging renewable energy technology with the potential to meet global energy demands. However, scaling up floating solar farms requires deploying large floating structures over extensive sea surfaces, posing significant engineering and environmental challenges. As floating solar scales to multi-hectare deployments offshore, evaluating their performance and environmental impact under uncertainty becomes a critical scientific and engineering challenge. The DigiOcean4Solar project aims to pioneer a Digital Ocean environment to enable fast and reliable simulations of wind-wave-structure interactions in floating solar farms. This research will provide the essential knowledge and computational tools needed to optimize the design and deployment of large-scale floating solar farms, ensuring their economic viability and environmental sustainability.

In this postdoctoral position, you will lead the development of a probabilistic, error-aware surrogate model capable of delivering fast, uncertainty-quantified predictions for complex multiscale–multiphysics processes in OFPV farms. This research will build upon a multi-scale and multi-physics numerical modeling framework, with the goal of enabling rapid and robust probabilistic assessments for design, optimization, and environmental impact studies. More precisely, you will be designing a new computational methodology that integrates adaptive and error-aware probabilistic surrogate/reduced order models that leverage multifidelity modelling, and goal-oriented numerical error estimation. The resulting surrogate model will map uncertain meta-ocean conditions to key quantities of interest for OFPV performance and sustainability.

You will join the Computational Multiphysics in Offshore Engineering (CMOE) group (https://tudelftcmoe.super.site/), a dynamic research team dedicated to developing state-of-the-art numerical methods for offshore renewable energy applications. The group specializes in computational modeling of fluid-structure interactions, wave-structure interaction and mooring systems for offshore renewable energies. You will be part of the Offshore Engineering section in the Hydraulic Engineering department, with leading experts in the field of offshore energy. You will actively participate in recurrent group meetings, write scientific articles, and give presentations at national and international conferences. If interested, you will be able to participate in teaching and supervision activities within the Faculty of Civil Engineering and Geosciences of Delft University of Technology.

A key aspect of this project will be collaboration with OFPV developers and industry partners. The research will be conducted in close cooperation with companies and organizations leading the development and deployment of offshore floating solar farms. This collaboration will ensure that the developed computational framework is aligned with real-world engineering challenges and can be applied directly to industry-scale OFPV projects.

Job requirements

We are acutely aware that we are a diverse society and not every talented applicant will have had the same opportunities to advance their careers. We therefore pledge to fully account for any particular circumstances that the applicants disclose (e.g. parental leave, caring duties, part-time jobs to support studies, disabilities etc.) to ensure an inclusive and fair recruitment process that does not rely purely on common research metrics.

The successful applicant will have:

• A PhD degree in Civil Engineering, Applied Mathematics, Mechanical Engineering, Maritime Engineering, Computer Science or a relevant domain.
• Expert knowledge in reduced order models (ROM) and/or surrogate models for the solution of partial differential equations. Research experience with integration of ROM and the Finite Element method is a plus.
• Demonstrated programming skills (Fortran/C++/Python/Julia), preferably in Julia.
• Knowledge in fluid-structure interaction problems and ocean energy technologies are considered a merit.
• Self-motivated, curiosity-driven, open to communicate and collaborate with peers.
• Excellent communications skills in English, both writing and speaking.
• Ability to work independently and self-driven in a multidisciplinary team

This position requires English proficiency to ensure that the candidate is able to communicate and interact well with colleagues and write scientific article.

Conditions of employment

Duration of contract is 30 months.

A job of 32-38 hours per week.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Additional information

For more information about this vacancy, please contact Oriol Colomés (j.o.colomesgene@tudelft.nl).

Application procedure

Are you interested in this vacancy? Apply via the application button below no later than 4 January 2026 and upload:

• A cover letter describing your motivation and qualifications for the position (1 page).
• Curriculum Vitae including three references and list of publications.
• Qualification evidence including PhD degree and transcripts.
• A link to the digital copy of PhD thesis.

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.