Bellarmine University is participating in the Rubin Legacy Survey of Space and Time (LSST) project. The Astrophysics group are part of the Rubin-LSST Dark Energy Science Collaboration (DESC) and have been contributing to DESC's Phosim (Photon Simulator) project. We are seeking a highly-motivated Postdoctoral Research Associate with a computational/observational research background in Cosmology or Astronomy or Astrophysics, to work for LSST-DESC focusing on exploration of dark energy, specifically on the development and testing of algorithms and software needed to pursue precise and accurate cosmological studies using weak lensing at the pixel level, quantitative assessment of potential biases in photometric redshift/cosmic shear estimators, and the development of solutions to meet the requirements for tomographic cosmic shear analyses.
The position is available as early as November 1, 2021 and will remain open until filled. Applicants are strongly encouraged to submit application by September 30, 2021. Competitive benefits including health insurance offered. This is Full-Time 3-Year Postdoctoral Research Associate. Position can be renewed annually based on the job performance by the postdoc's supervisor.
Candidates must have a Ph.D. in Astronomy or Astrophysics or Cosmology or Physics by the starting date of the appointment. Candidates must have strong computational abilities and coding skills and experience. Work experience in Python, Jupyter notebook, SQL and code development in HPC Linux Condor environment is desirable. Data analysis experience in the context of cosmology or astrophysics or astronomy is required. Prior research experience in galaxy clusters, weak lensing and/or analysis of photometric datasets is an asset. Familiarity with the Rubin Science Platform (RSP), Rubin-LSST pipeline design and development, and knowledge of machine learning techniques is a plus. Interested applicants should submit a letter of interest, CV, and statement of research background and past research experience. In addition, applicants should arrange for three letters of recommendation to be submitted by the references directly to Professor Akhtar Mahmood at [email protected]. One of the three letters must be from the candidate's Ph.D. thesis advisor.