DIRAC Postdoctoral Positions

The DIRAC Institute in the Department of Astronomy at the University of Washington is seeking applicants with a strong research record in the development of statistical techniques or algorithms for analyzing large astrophysical data sets for two postdoctoral positions.

AstroML: The first position is to help in the development of the second edition of astroML (http://astroml.org) a popular Python-based machine learning package for astrophysics. New components we are incorporating within astroML include methodologies from deep learning and hierarchical bayesian statistics. Special emphasis will be placed on building a broader community and making astroML a sustainable open-source project. The successful candidate will lead these activities, including the application of the new codes to dataset available to UW researchers.

Time Series Data: The second position is to develop new approaches for analyzing astronomical time series data using modern computational frameworks. The goal of this framework will be to enable science with the ZTF and LSST data sets. Promising applicants should possess an interest in time domain science and experience or interest in the use of databases and large scale compute platforms such as Spark, Dask, or similar. Good Python skills, and experience with machine learning libraries, image processing of astronomical images, or astronomical databases are desirable.

The DIRAC Institute is a newly formed center for data intensive astrophysics at the University of Washington. The Institute consists of six faculty and senior fellows, and over 20 postdoctoral researchers and research scientists. It has active research programs in Cosmology, Solar System science, Milky-Way structure, the Variable and Transient universe, andAstronomical Software.

The University of Washington is a partner in the Zwicky Transient Facility (ZTF) project, a new time-domain survey which will begin operations in early 2018. The UW is a founding partner of the LSST project, and leads the construction of its time domain and solar system processing pipelines. Other research activities at UW/DIRAC include topics in extragalactic science, as well as the understanding the structure, formation, and evolution of the Milky Way using large surveys (SDSS, WISE, PanSTARRS PS1, and others).

A Ph.D. degree in astronomy, physics, computer science, or a related subject is required. The initial appointment is for two years, renewable up to three years, and offers competitive salary and benefits. The appointments are available immediately and are expected to start no later than September 2018.

Applicants should submit a curriculum vitae, description of research interests (with links to Github if relevant) and arrange for three letters of reference to be submitted to Nikolina Horvat at horvat@uw.edu with subject line “DIRAC postdoc application (your name)”. Applications will be accepted until the positions are filled, to assure full consideration, please send your application by Dec 31st 2017

For detailed information about the benefits available through the University of Washington, including dental, medical and disability insurance, retirement, and childcare centers, see the University of Washington benefits page: https://www.washington.edu/admin/hr/benefits/.

The DIRAC Institute is a community of people with diverse interests and areas of expertise, engaged in the understanding of our universe through the analysis of large and complex data sets. We are an open, ethical, highly engaged and collaborative community based on trust, transparency and mutual respect. We believe in providing a welcoming and inclusive environment, in the importance of quality of life, in embracing diversity, in making a difference and having fun.

2018-11-09 Seminar: Sjoert van Velzen

When: November 9, 2018 @ 11:00am

Where: PAB, WRF Data Science Studio, 6th floor, seminar room (C607)

Sjoert van Velzen is James Arthur Postdoctoral Fellow at the CCPP, NYU. He also has a partial affiliation at UMD, where he works with the exciting data from the Zwicky Transient Facility.

Stellar tidal disruptions flares: new tools for black hole astrophysics 

The tidal disruption of a star by a massive black hole is a rare event that results in a spectacular flare of electromagnetic radiation. Visible from infrared to X-ray wavelengths, tidal disruption flares are a unique probe to study massive black holes and the nucleus of their host galaxies. The advent of optical transient surveys has accelerated this relatively young field; the detection rate keeps increasing and we are discovering many new—and often unexpected—results. I will present some of these discoveries, including recent results from the Zwicky Transient Facility. 

DIRAC Postdoctoral Fellow Positions

We invite applications for up to two DIRAC Research Associates in the Department of Astronomy at the University of Washington. These 3-year positions are available to promising, early-career researchers who

  • Are interested in working on scientific research that complements or extends the current active research programmes at DIRAC (Cosmology, Solar System science, Milky-Way structure, the Variable and Transient universe, Astronomical Software, extragalactic science, and the understanding the structure, formation, and evolution of the Milky Way using large surveys like SDSS, WISE, PanSTARRS1, ZTF and others). We welcome research proposals from outside these areas that show how their work connects to DIRAC’s areas of expertise.
  • are excited to work with new data sets like those produced for example by Gaia, ZTF and LSST
  • are interested in exploring and applying new statistical and computational techniques to these data sets, and how to extend current methodology to be applicable in the era of big data
  • are enthusiastic about collaborating with researchers across all areas of astrophysics and are curious about building connections with scientists from other fields like computer science and statistics.

Applicants should demonstrate excellence in research that either complements or builds upon ongoing research directions within the DIRAC Institute. Successful candidates will work with the current DIRAC faculty and researchers to develop their own programs of research and innovation.

The DIRAC Institute is a recently formed center for data intensive astrophysics at the University of Washington. The Institute consists of six faculty and senior fellows, and over 20 postdoctoral researchers and research scientists. The University of Washington is a partner in the Zwicky Transient Facility (ZTF) project, a new time-domain survey now in routine operations. The UW is a founding partner of the LSST project, and leads the construction of its time domain and solar system processing pipelines.

Qualifications: A Ph.D or foreign equivalent degree in astronomy, physics, computer science, or a related subject is required. The initial appointment is for two years, renewable for a third year, and offers competitive salary and benefits. The appointment is expected to start no later than September 2019.

Application Instructions: Applications should be submitted online through the UW Interfolio FS module . Applicants should submit a cover letter, curriculum vitae, research statement (maximum length 3 pages, addressing both current work and laying out research ideas for the 3-year fellowship) as well as contact information for three letters of recommendation. Candidates should address in their application how their work potentially complements, connects to, or extends current research efforts at DIRAC, or indicate how they would benefit from expertise available at DIRAC. 

We encourage candidates to highlight work and achievements related to data-intensive astronomy that they are enthusiastic about, but do not easily fit within traditional metrics of academic success (e.g. open-source software development, development of teaching or outreach materials, diversity work, etc).

Please apply by December 10th, 2018 for full consideration, but applications will be accepted until the positions are filled. 

Included Benefits: For detailed information about the benefits available through the University of Washington, including dental, medical and disability insurance, retirement, and childcare centers, see the University of Washington benefits page: https://www.washington.edu/admin/hr/benefits/.
 
 

Quanta Magazine’s Interview with Prof. Mario Juric

Quanta Magazine spoke with prof. Mario Jurić about how the swell of data is changing what it means to be an astronomer.

Prepping for a Flood of Heavenly Bodies

Just as mathematics transformed physics from a philosophy into a science, data and computation are transforming science today, says Mario Jurić. He’s leading the push to get astronomy ready for the torrents of data that are about to flow.
 
Read the article here.

2018-10-29 Seminar: Michael Koss

When: October 29, 2018 @ 12:30pm
Where: PAB, WRF Data Science Studio, 6th floor
 
Dr. Michael Koss is currently funded through NASA satellite grants and resides in Kirkland, Washington. Prior to this he was an Ambition fellow in Zurich, Switzerland and a postdoctoral fellow in Honolulu, Hawaii.  He obtained his PhD in 2011 from University of Maryland with a NASA fellowship where he worked on the Swift Satellite and balloon missions.  He is heavily involved with NASA satellites and is part of the Swift BAT science team and the NuSTAR AGN science team as well as newly proposed X-ray missions such as Lynx, AXIS, and STROBE-X.  More info about him and his research can be found at his personal website (https://www.michael-koss.com/).
 
The Swift BAT AGN Survey-14 Years of Surveying the Sky 
 
The Neil Gehrel’s Swift Satellite was launched with a primary focus on localizing Gamma Ray Bursts using it’s on board X-ray and UV/optical telescopes.  In the nearly 14 years since launch, Swift has expanded significantly beyond the realm of GRBs with an unequaled Target of Opportunity machine with rapid Xray/UV transient follow-up.  The  Burst Alert Telescope (BAT) instrument on the Swift satellite has also surveyed the sky to unprecedented depth, increasing the all sky hard X-ray sensitivity by a factor of more than 40 compared to previous satellites.  I will review the unique ability BAT has provided to survey AGN using the ultra hard X-rays. In particular, what insights does high energy selection of AGN provide about obscured black hole growth and its relation to the host galaxy, the AGN torus, and time variability of AGN.  Finally, I will present the BAT AGN Spectroscopic Survey (BASS, http://www.bass-survey.com) whose goal is to complete the first large (>1000) survey of hard X-ray selected AGN with X-ray properties, black hole masses and accretion rates, stellar masses, gas fractions, and radio properties.  
 
 

2018-10-25 Astronomy Colloquium: Stephen Portillo

When: October 25, 2018 @ 4:00pm
Where: PAA A102, with refreshments at 3:45PM
 
This week’s colloquium speaker is our own Stephen Portillo. 
 
Counting Stars: Developing Probabilistic Cataloging for Crowded Fields     
 
The depth of next generation surveys poses a great data analysis challenge: these surveys will suffer from crowding, making their images difficult to deblend and catalog. Sources in crowded fields are extremely covariant with their neighbors and blending makes even the number of sources ambiguous. Probabilistic cataloging returns an ensemble of catalogs inferred from the image and can address these difficulties. We present the first optical probabilistic catalog, cataloging a crowded Sloan Digital Sky Survey r band image cutout from Messier 2. By comparing to a DAOPHOT catalog of the same image and a Hubble Space Telescope catalog of the same region, we show that our catalog ensemble goes more than a magnitude deeper than DAOPHOT. We also present an algorithm for reducing this catalog ensemble to a condensed catalog that is similar to a traditional catalog, except it explicitly marginalizes over source-source covariances and nuisance parameters. We also detail efforts to make probabilistic cataloging more computationally efficient and extend it beyond point sources to extended objects. Probabilistic cataloging takes significant computational resources, but its performance compared to existing software in crowded fields make it a enticing method to pursue further.

Visitors: Kathryn McKeough

Kathryn McKeough is a Ph.D. candidate in the Department of Statistics at Harvard University. She does research as a member of both the CHASC: Astrostatistics Group and the Sports Analytics Lab at Harvard. Her Tuesday, October 23rd, 2018 talk at 12pm will be on Defining Regions that Contain Complex Astronomical Structures.

Seminar on Tuesday, October 23, 2018 at 12:00pm

2018-10-23 Seminar: Kathryn McKeough

When: October 23, 2018 @ 12:00pm
Where: PAB, WRF Data Science Studio, 6th floor, Seminar Room
 
DIRAC is pleased to welcome Katy McKeough as a visitor next week.  

Katy is a Ph.D. candidate in the Department of Statistics at Harvard University. She does research as a member of both the CHASC: Astrostatistics Group and the Sports Analytics Lab at Harvard. Her Tuesday 12pm talk will be on Defining Regions that Contain Complex Astronomical Structures.

Defining Regions that Contain Complex Astronomical Structures

Astronomers are interested in delineating boundaries of extended sources in noisy images. An example is finding outlines of a jet in a distant quasar. This is particularly difficult for jets in high redshift, X-ray images where there are a limited number of pixel counts. Using Low-counts Image Reconstruction and Analysis (LIRA), Stein et al. 2015 and McKeough et al. 2016 propose and apply a method where jets are detected using previously defined regions of interest (ROI). LIRA, a Bayesian multi-scale image reconstruction, has been tremendously successful in analyzing low count images and extracting noisy structure. However, we do not always have supplementary information to predetermine ROI and the size and shape can greatly affect flux/luminosity. LIRA is also unaware of correlations that may exist between adjacent pixels in the real image. In order to group similar pixels, we impose a successor or post-model on the output of LIRA. We adopt the Ising model as a prior on assigning the pixels to either the background or the ROI. From the posterior of this model, we are able to delineate probabilistic boundaries. This method has been applied to the jet data as well as simulations and appears to be capable of picking out meaningful ROIs.

 

Estimating the Milky Way’s Mass via Hierarchical Bayes: A Blind Test on MUGS2 Simulated Galaxies

DIRAC Researcher, Gwendolyn Eadie, published a paper in the Astrophysical Journal.

Published on September 24, 2018.

Estimating the Milky Way’s Mass via Hierarchical Bayes: A Blind Test on MUGS2 Simulated Galaxies

Abstract

In a series of three papers, Eadie et al. developed a hierarchical Bayesian method to estimate the Milky Way Galaxy’s mass given a physical model for the potential, a measurement model, and kinematic data of test particles such as globular clusters (GCs) or halo stars in the Galaxy’s halo. The Galaxy’s virial mass was found to have a 95% Bayesian credible region (c.r.) of (0.67, 1.09) × 1012 ${M}_{\odot }$. In the present study, we test the hierarchical Bayesian method against simulated galaxies created in the McMaster Unbiased Galaxy Simulations 2 (MUGS2), for which the true mass is known. We estimate the masses of MUGS2 galaxies using GC analogs from the simulations as tracers. The analysis, completed as a blind test, recovers the true M 200 of the MUGS2 galaxies within 95% Bayesian c.r. in 8 out of 18 cases. Of the 10 galaxy masses that were not recovered within the 95% c.r., a large subset have posterior distributions that occupy extreme ends of the parameter space allowed by the priors. A few incorrect mass estimates are explained by the exceptional evolution history of the galaxies. We also find evidence that the model cannot describe both the galaxies’ inner and outer structure simultaneously in some cases. After removing the GC analogs associated with the galactic disks, the true masses were found more reliably (13 out of 18 were predicted within the c.r.). Finally, we discuss how representative the GC analogs are of the real GC population in the Milky Way.

PDF

Article

2018-09-28 DIRAC Astronomy Open-source Sprint

DIRAC Institute has the 1st Astronomy Open-source Sprint, Sep 28, 2018 at the University of Washington.

When: September 28, 2018 @ 1:00-4:30pm
Where: PAB, WRF Data Science Studio, 6th floor, Meeting Room
 
Maintainers of several projects (e.g. astropy, astroquery, astroplan, stingray, etc) have committed to attend the sprints and will help with getting started and other practicalities. 
 
Contributions can be of different types from issue triaging, implementing bug and documentation fixes to adding new features. Please bring your laptop, and if you have any issue in mind (otherwise there are also plenty to choose from e.g. here: https://github.com/astropy/astropy/issues).  
 
Facilitated by Brigitta Sipocz.

2018-09-07 Seminar: Lia Sartori

When: September 7, 2018 @ 11:00am
Where: PAB, WRF Data Science Studio, 6th floor
 
Lia Sartori from the ETH Zürich Institute for Particle Physics and Astrophysics, will be discussing variability in active galactic nuclei. 
 
A study of active galactic nuclei variability on multiple timescales
 
Variability is ubiquitous in active galactic nuclei (AGN) and can be observed or inferred at all timescales, from hours to billions of years. In this talk I will first illustrate how spatially resolved optical spectroscopy, combined with high quality X-ray data, can be used to probe AGN variability on > 10^4 yr timescales. I will then present a compilation of variability measurements, covering many orders of magnitude both in time lags and variability amplitude, which provides an overview of the variabiltiy phenomena. This compilation includes ensemble studies, which characterise the mean variability among the AGN population, as well as measurements for single objects such as the changing look AGN, the Voorwerpjes galaxies, and our own Sagittarius A*. Finally, I will present a framework which allows us to test if and how variability in different AGN and at different timescales can be linked and explained based on the distribution of the Eddington ratio (ER) among the galaxy population. Specifically, we propose a forward modelling approach to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and the power spectral density (PSD) of the ER distribution. At the end of the talk I will also discuss possible applications of our model, e.g. for understanding changing look AGN or planning future time domain surveys.