Alexander Heinlein

Delft University of Technology (TU Delft) is offering two fully funded PhD positions as part of the RAPID-Wind project, funded by the Dutch Research Council (NWO). The positions are supervised by Assistant Professor Alexander Heinlein and Oriol Colomés. The research focuses on the intersection of high-fidelity simulations, machine learning, and offshore wind energy, aiming to address real-world engineering challenges and contribute to the global energy transition. The first PhD position centers on high-fidelity simulations of innovative offshore wind foundations, leveraging advanced computational science techniques to improve the design and performance of wind energy infrastructure. The second position involves developing neural network-based surrogate models for offshore wind foundations, integrating machine learning approaches to accelerate and enhance engineering analyses. Applicants should have a strong background in computational science, engineering, mathematics, or related fields, with experience in high-fidelity simulations, machine learning, or numerical analysis considered a significant advantage. The ability to work collaboratively in a multidisciplinary environment and a motivation to contribute to sustainable energy solutions are essential. Proficiency in English is required, and further eligibility details are available on the official TU Delft careers pages. Both positions are fully funded, offering a competitive salary and benefits in accordance with Dutch PhD standards. The research is hosted at TU Delft, a leading institution in engineering and technology, located in the Netherlands. The application deadline is March 22, 2026. Interested candidates should review the detailed job descriptions and submit their applications via the official TU Delft online portal. For more information, candidates can contact the supervisors or visit the provided links. Key research areas include offshore wind energy, computational science, machine learning, high-fidelity simulations, neural networks, surrogate modeling, and the energy transition. The RAPID-Wind project provides an excellent opportunity for motivated students to engage in impactful research at the forefront of sustainable engineering.

Postdoctoral opening at Delft University of Technology in AI-Driven Biofabrication and Process Control . This position sits at the intersection of scientific machine learning , modeling , and control , with the goal of developing a next-generation AI-driven biofabrication toolbox as part of the NWO (Dutch Research Council) Perspectief project FAB4FUTURE . The research focuses on making the production of living tissues and materials more reliable and scalable, with applications in improved disease models and more sustainable food production. The project is highly collaborative and involves a consortium including Maastricht University , UMC Utrecht , Universiteit Utrecht , Zuyd University of Applied Sciences , and industry partners such as Mosa Meat , Poietis , Demcon , ReGEN Biomedical , Scinus Cell Expansion B.V. , xolo , Axolotl Biosciences , and RDI RDInnovation . Researchers mentioned in connection with the project include Carlos Miguel Domingues Mota , Jos Malda , Lorenzo Moroni , Matthew Baker , Mylene de Ruijter , Paul Wieringa , and Riccardo Levato . The post is shared by Alexander Heinlein , Assistant Professor Numerical Analysis at TU Delft. This is a postdoc opening, not a scholarship call. The post does not specify salary, stipend, or tuition details in the provided text. Application deadline: 8 June 2026 . Interested candidates should use the TU Delft careers page and follow the application instructions in the official job posting.