Position Summary
The National Radio Astronomy Observatory invites applications for a next-generation VLA (ngVLA) Configuration Research Associate. The successful applicant will work within the ngVLA project team on a detailed investigation of the configuration and image simulation work with the ngVLA.
The position is initially available for two years starting April 15, 2018 (or sooner), with a third year contingent on progress and available funding. Funding for the successful applicant to attend and present at domestic and international meetings will be available.
The position will be based at either the Science Operations Center in Socorro, NM on the campus of New Mexico Institute of Mining and Technology (www.nmt.edu) or at the NRAO Headquarters in Charlottesville, VA on the grounds of the University of Virginia (www.virginia.edu). In addition to competitive pay,
Job Duties Summary
The successful candidate will be an essential part of the ngVLA effort as the project prepares for the Astronomy 2020 Decadal Survey. The primary focus will be performing a high‐level study that continues development of a practical configuration for the array. This may include variations on the current baseline configuration to add longer baselines or address performance deficiencies identified throughout the study, as well as the inclusion of a short-spacing array to help fill in missing baselines shorter than the ngVLA dish diameter. This study should also include an analysis of the required data weights to approximate Gaussian synthesized beams at different angular scales to maximize image fidelity. This study is expected to be carried out in close collaboration with the imaging algorithm development team at NRAO. The appointee will be allocated time to carry out independent research.
The full description of the position and application instructions are available at this URL http://jobs.jobvite.com/nrao/job/oFO65fwo.
Minimum Education
PhD in astronomy or related field.
Minimum Experience
Observational astronomy, data analysis.
Preferred Experience
A strong background in interferometry; skilled at using python and CASA for data analysis and public tool creation; a strong record of independent research.