Are you excited by gravitational waves, cosmology, and modern AI-based analysis techniques? Do you enjoy developing new methods and working closely with theorists and LISA instrument and data-analysis teams? Join the GRAPPA research center at the University of Amsterdam to tackle the global analysis of data from the next-generation Laser Interferometer Space Antenna (LISA) and help shape the future of gravitational-wave cosmology. Closes on February 15th 2026.
We are seeking an enthusiastic PhD candidate to develop cutting-edge, AI-driven inference methods for next-generation gravitational-wave astronomy, with a focus on cosmology and astroparticle physics. The position is based at the University of Amsterdam within the GRAPPA Center of Excellence, where you will join the research group of Dr. Christoph Weniger and work in close collaboration with an international network of theorists, machine-learning and AI experts, and LISA instrument and data-analysis teams, at the interface of fundamental physics and modern data science.
The PhD project is centered on the analysis of data from the Laser Interferometer Space Antenna (LISA) and addresses key challenges such as the global inference of large populations of overlapping gravitational-wave sources and stochastic backgrounds. The ultimate goal is to extract new information about the early Universe and fundamental physics—including inflationary processes, dark matter, and dark energy—from LISA’s rich gravitational-wave data.
What you will do
You will work as part of a strong, collaborative research team on the development and application of AI-based inference methods for gravitational-wave cosmology, focusing on complex, high-dimensional LISA data.
A central element of the project is the use of simulation-based inference (SBI)—a rapidly developing alternative to classical likelihood-based data analysis enabled by recent advances in deep learning. Within the LISA context, these methods are developed in a complementary way to existing likelihood-based and pipeline-driven efforts aimed at achieving a global fit of the data, providing new tools to address LISA’s computational and statistical challenges.
In particular, you will work on sequential, hierarchical, and population-level inference methods for LISA data analysis. Your work will result in publications in leading peer-reviewed journals and presentations at international conferences. You will also contribute to open-source research software and participate in the supervision of Bachelor and Master students.
Tasks and responsibilities:
- Conducting independent research in gravitational-wave cosmology and data analysis, leading to publications in international peer-reviewed journals;
- Developing and applying AI-driven inference methods for LISA data;
- Contributing to open-source software for AI-driven gravitational-wave analysis;
- Presenting research results at international conferences and workshops;
- Assisting in the supervision of Bachelor and Master students, including co-supervision of theses and tutoring.
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