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 firstname.lastname@example.org 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.
Science has become a big-data endeavor. But scientists are not universally adept in “data science” — the computing and statistical skillsets needed to handle, sort, analyze and draw conclusions from big data. The shortage of know-how in data science can hamper research, medicine and even private industry
A new paper led by Daniela Huppenkothen, Associate Director of DiRAC, was just published in the Proceedings of the National Academy of Sciences on how we can learn these skills by working collaboratively. With a team of researchers from the University of Washington, New York University and the University of California, Berkeley she developed an interactive workshop in data science for researchers at multiple stages of their careers. The course format, called “hack week,” blends elements from both traditional lecture-style pedagogy with participant-driven projects. The most recent was a neuroscience-themed event held in July on the UW campus organized by Ariel Rokem, a data scientist with the UW eScience Institute. As the team reports in a their paper published Aug. 20, participants rated the hack weeks as opportunities to learn about new concepts, foster new connections, share data openly, and develop skills and work on problems that will positively affect their day-to-day research lives.
Read more about this in the full UW press release
When: August 3, 2018 @ 3:00 pm
Where: PAB, WRF Data Science Studio, 6th floor
David A van Dyk, Statistics Section, Department of Mathematics, Imperial College London
Quantifying Discovery in Astro/Particle Physics: Frequentist and Bayesian Perspective
DIRAC Institute is hosting the 1st LSST Solar System Readiness Sprint, July 10-12, 2018 at the University of Washington. This is a LSST Solar System Science collaboration workshop to begin getting ready for LSST solar system science.
Live coverage is available here.
Astronauts, astronomers, scientists, students, teachers, and interested citizens around the world are coming together at this very moment to learn about and discuss asteroids.
UW is participating in Asteroid Day, a global day of education to help protect Earth from potentially hazardous asteroid. The movie below shows how UW LSST and DIRAC’s astronomical software group is assisting that effort by making the LSST an unprecedented asteroid discovery machine.
June 27th-29th, 2018
I work on Galactic Archaeology, which is the study of the structure and evolution of the Milky Way. I did my PhD at New Mexico State University working with Jon Holtzman and Jo Bovy with the APOGEE survey, which is an SDSS3 and SDSS4 spectroscopic survey of several hundred thousand red giants across the Milky Way. I spent two years working in Nice at the Observatoire de la Cote d’Azur with the Gaia-ESO and AMBRE projects, which have spectroscopic observations of tens of thousands of stars throughout the Galaxy.
Currently, I am an ASTRO 3D fellow working at the University of Sydney with the GALAH Survey. GALAH is a large-scale spectroscopic survey of 500,000 stars throughout the Milky Way, and aims to measure chemical abundances for 30 different elements to map and chemically tag the stellar populations of the Galaxy. In my talk, “Chemical Cartography of the Milky Way”, I will discuss the chemodynamic properties of different stellar populations throughout the disk and how they vary with location.
I attached a figure of some preliminary results from the GALAH survey, showing how the chemical structure of the disk varies from the inner Galaxy to the edge of the disk.
Dr. Eadie completed her doctoral studies at McMaster University under the supervision of Dr. William Harris. In her thesis entitled “Lights in Dark Places: Inferring the Milky Way Mass Profile using Galactic Satellites and Hierarchical Bayes”, she developed a high-level statistical method to derive the mass and mass distribution within astrophysical systems. Mass is a fundamental variable driving the evolution of galaxies like our Milky Way, but it is notoriously difficult to measure due to the fact that it is dominated by the dark matter extending well beyond the visible starlight. This challenge is compounded by incomplete data on the positions and velocities of “tracer particles” such as stars, star clusters and dwarf satellites scattered through the galaxy’s halo. Dr. Eadie developed a powerful Bayesian formulation of the problem combined with Markov Chain Monte Carlo calculations of the relevant parameters in the problem and their probability distributions. Her formulation also included a hierarchical treatment of measurement uncertainties for each tracer. She used it to place a new constraint on the mass profile and total mass of the Milky Way, and it will be a very powerful tool in the exploitation of future very large datasets from the Gaia mission and the Large Synoptic Survey Telescope (LSST). .
CASCA congratulates Dr. Eadie on the receipt of the 2018 Plaskett medal for her groundbreaking work to shed light on the dark side of our Milky Way galaxy and other corners of the Universe.
Read full announcement here.
Dr. Sarah Greenstreet and Bryce Bolin named first senior research fellows.
SILICON VALLEY, CA/SEATTLE WASH. (May 17,2018) — The Asteroid Institute has announced new appointments in the field of planetary defense and asteroids. Dr. Sarah Greenstreet and Bryce Bolin have been selected to serve as the first Senior Research Fellows, under the direction of Dr. Ed Lu, Executive Director of the Asteroid Institute, three time NASA astronaut, former Google executive and co-founder of B612 Foundation. The fellows study the application of new technologies for the discovery, tracking and potential deflection of asteroids.
Read full article here.
How number crunchers could help crack the cosmological mystery of dark energy
BY ALAN BOYLE on May 15, 2018 at 9:08 pm
Big data just might give astronomers a better grip on the answer to one of the biggest questions in physics: Exactly what’s behind the mysterious acceleration in the expansion rate of the universe, also known as dark energy?
Read the full article here.
Petar Zečević is a PhD student from University of Zagreb, Croatia. He has been working in the software industry for more than 15 years, as a full-stack developer, consultant, analyst, and team leader. Petar is the author of Spark in Action book (Manning, September 2016). He also gives talks on Apache Spark, organizes monthly Apache Spark Zagreb meetups, and has several Apache Spark projects behind him.