Postdoctoral Fellow in Machine Learning for Astrophysics & Cosmology

Postdoctoral Fellow in Machine Learning for Astrophysics & Cosmology

Stockholm University

Stockholm, Sweden

Project description

We seek outstanding postdoctoral researchers, with background in computational, theoretical and/or observational projects, to develop and deploy cutting-edge machine-learning and AI methods for astrophysics and cosmology, enabling precision tests of fundamental physics with current and next-generation galaxy and time-domain surveys. You will work closely with our teams on the Rubin Observatory ‘s LSST, Euclid, ZTF, and LS4.

Main responsibilities

• Field-level inference and simulation-based inference for cosmology;
• Neural emulators/surrogate models for accelerated forward modelin;
• Differentiable simulations and probabilistic programming for end-to-end pipelines;
• Robust uncertainty quantification, systematics mitigation, and domain adaptation;
• ML for time-domain discovery and characterization (e.g., transients, time-delay cosmography).

Qualification requirements

In order to qualify for a Postdoctoral position, applicants are required to hold a Swedish doctoral degree or an equivalent relevant degree from another country. The degree must have been completed no later than when the employment decision is made.

Assessment criteria

It is considered an advantage if the doctoral degree or an equivalent degree was completed no more than three years prior to the application deadline. Under special circumstances, an older degree may also be an advantage. Special circumstances refer to sick leave, parental leave, elected positions in trade unions, service in the total defense, or other similar circumstances, as well as clinical attachment or service/assignments relevant to the subject area.

In the appointment process, special attention will be given to research skills in astrophysics and cosmology, programming, and machine learning. The position also requires fluency in spoken and written English.