Project description

We are seeking a postdoctoral fellow to contribute to the Manticore Digital Twin of the Universe program, developing and applying advanced computational methods to study cosmic structure. The project is funded by a Simons Foundation grant and is part of the international collaboration Learning the Universe (www.learning-the-universe.org), which develops cutting-edge techniques to reconstruct the initial conditions of our Universe and test fundamental physics with current and next-generation cosmological surveys.

Possible research directions include, but are not limited to:

• Field-level inference and generative modeling of large-scale cosmic structure
• Simulation-based inference, numerical simulations, and neural emulators for accelerated forward modeling
• Advanced data-intensive machine learning and AI techniques for survey analysis
• Applications to major international surveys, including LSST (Rubin Observatory), Euclid, and ZTF.

The candidate will join the Simons Collaboration, with opportunities for multidisciplinary collaborations with researchers at participating institutions: Columbia University, Lawrence Berkeley National Lab, Harvard University, Flatiron Institute, Institut Astrophysique de Paris, Université de Montréal, Princeton University, Carnegie Mellon University, and MPA Garching.

The position is hosted at the Oskar Klein Centre for Cosmoparticle Physics (OKC) in Stockholm, a vibrant research environment with more than a hundred researchers working in theory and experiment across astronomy, astrophysics, cosmology, and particle physics. OKC hosts active programs on dark matter, dark energy, structure formation, transients, and multimessenger astrophysics. Postdoctors are also welcome to participate in Nordita’s Scientific Programs, which bring together leading experts to work on focused topics, and will be members of the Aquila Consortium (www.aquila-consortium.org), an international collaboration developing novel data science techniques to study fundamental physics with cosmic structures.

In addition, the postdoc will be part of the Excellence Dark Universe Centre and Technology Enabler (EDUCATE), uniting researchers at Stockholm University and KTH Royal Institute of Technology to develop next-generation analysis techniques and machine learning methods for exploring dark matter, dark energy, and cosmic structure formation.

We welcome candidates who be inspires by the intersection of computational technology, numerical simulations, and fundamental physics, whether their expertise is in machine learning, numerical modeling, or both, and who want to develop innovative methods while advancing our understanding of the Universe.

Main responsibilities

The position involves research on developing and applying cutting-edge machine learning, data science, and computational methods to study the large-scale structure of the Universe using cosmological survey data.

Postdoctoral researchers at OKC are encouraged and supported to lead visible research projects within major international collaborations and to contribute to the broader scientific community through innovative methodology development, survey data analysis, and interdisciplinary collaborations.

Candidates are welcome to participate in ongoing activities within the observational and experimental programs at OKC (e.g., DESC/LSST, ZTF, LS4, LHC/ATLAS, the ALPHA axion experiment), as well as cosmological and astroparticle simulations, the BORG field-level inference framework, and the Manticore Digital Twin of the Universe program.

The position may also involve international travel to partner institutions in Europe and the United States. Applicants with backgrounds in cosmology, statistical inference, machine learning, numerical simulations, or related fields are all encouraged to apply.

Ref. No. SU FV-4045-25

Closing date: 7 January 2026

Complete information here