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Active FELLOWSHIP AWARD National Science Foundation (US)

Postdoctoral Fellowship: AAPF: Combining Machine Learning and Milky Way Stellar Spectroscopic Surveys to Probe our Galaxy's Complex Chemical Past and Present

$1.1M USD

Funder National Science Foundation (US)
Recipient Organization Manea, Catherine
Country United States
Start Date Sep 01, 2024
End Date Aug 31, 2027
Duration 1,094 days
Number of Grantees 1
Roles Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2401638
Grant Description

Catherine Manea is awarded an NSF Astronomy and Astrophysics Fellowship to carry out a program of research and education at Columbia University. Manea will leverage the power of machine learning and the upcoming surveys that will map the entire sky to better understand how the chemical composition of our Milky Way galaxy has changed over time. For the educational component of her project, Manea will play a leading role in the newly founded StreamTeam TNG program which provides research experience to New York City undergraduate students with a focus on community college students.

Galactic chemical evolution (GCE) is a direct consequence of the star formation history of our Galaxy, and constraining GCE provides direct insights into the build-up and evolution of our Milky Way’s stellar populations. Manea will conduct three complementary projects that take advantage of machine learning and the upcoming Sloan Digital Sky Survey (SDSS) and GALactic Archaeology with HERMES (GALAH) data releases to place key empirical constraints on GCE previously inaccessible due to limitations in data quantity.

Her research program will approach this from two opposing angles by measuring 1) the chemical diversity of field stars and 2) the chemical similarity of stars born together.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

All Grantees

Manea, Catherine

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