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Skills
Summary
Work History
Education
Nina Bonaventura, PhD

Nina Bonaventura, PhD

Astrophysicist (https://orcid.org/0000-0001-8470-7094)
Copenhagen
Skills

Scientific software development

Python programming

Research program planning

Quantitative data analysis

Machine/deep learning

Scientific documentation

Astronomical instrumentation

Telescope operation

Astronomical image analysis

Astronomical signal processing

Flexible & Adaptable

Multitasking abilities

Collaboration

Summary

In my daily life as an astrophysicist, I call on many years of academic and professional experience in physics, astronomy, and computational science applications. Throughout this time I have gained expertise in the processing, simulation, manipulation, optimization, and scientific analysis of multiwavelength astronomical data sets obtained with various types of astronomical imagers and spectrometers, on both ground- and space-based telescope observatories.

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I have worked as an astronomer in support of two NASA space missions, Chandra and JWST, where I have devoted a significant amount of time to the development of astronomical data analysis algorithms and associated (Python) software, including award-winning NASA public documentation, in addition to scholarly scientific research.

* * *

These plentiful and varied experiences - in both team and solo environments and with professionals from diverse academic backgrounds and career levels - have equipped me with the confidence and skill set necessary to be a highly adaptable computational physical scientist in a number of scientific and technical fields, including but not limited to: multiwavelength extragalactic astrophysics research, imagery analysis, applied machine learning, signal processing, scientific algorithm development and programming.

Work History

Astrophysicist (JWST/NIRSpec Expert)

Cosmic Dawn Center (DAWN), Niels Bohr Institute
2017-12 - Current

As an astrophysics post-doctoral researcher at the Cosmic Dawn Center (DAWN), I work alongside Dr. Peter Jakobsen on the scientific optimization of astronomical data to be obtained by the premier Near-infrared Spectrometer (NIRSpec) onboard NASA's James Webb Space Telescope (JWST), for the JWST/NIRSpec Guaranteed Time Observer (GTO) Team, associated JWST Advanced Deep Extragalactic Survey (JADES) collaboration, and JWST/NIRSpec Commissioning Team.

  • JWST/NIRSpec GTO Team Member: In this role I contribute to the development of scientific algorithms and associated software (Python) applications (N.R. Bonaventura & P. Jakobsen, in prep.; internal private documents available upon request) that optimize the NIRSpec scientific data return for the NIRSpec GTO and JADES science programs. I will also lead the JADES scientific research efforts and publication(s) of JWST spectroscopic science on high-redshift, massive quiescent galaxies, based on expertise in galaxy SED modeling and spectroscopic analysis.
  • ESA JWST/NIRSpec Commissioning Team Member: As a result of my contribution to the NIRSpec GTO science program, I was granted and completed a contract with the European Space Agency (ESA) to join the JWST/NIRSpec Commissioning Team to monitor and test crucial scientific functions of the NIRSpec instrument during its six-month commissioning phase, post-launch in December 2021. I fulfilled the role of Quick-look Scientific Analyst of JWST raw data as it arrived on Earth at the Space Telescope Science institute (STScI) JWST Mission Operations Center. I also prepared formal commissioning procedures to test various aspects of the NIRSpec performance that rely on the use of algorithms and specialized software personally contributed (N.R. Bonaventura & P. Jakobsen, in prep.; internal private documents available upon request).

Astrophysics and Applied Machine Learning

Dark Machines
2020-12 - Current

In addition to the scientific activities I perform for DAWN and ESA, I conduct scientific reasearch with a group of physicists and Data Scientists in the area of applied machine learning in astrophysics. Here, I lead the analysis of both simulated and real astronomical photometric survey images, which helps to guide the application of a novel computational ML approach to accurately and reliably extract the dark matter mass and distribution from the galaxies in these images (Martinez et al. 2022: https://arxiv.org/abs/2111.08725).

Astrophysics Data Specialist & Researcher

Chandra X-ray Center (CXC), NASA Smithsonian Astrophysical Observatory
2007-12 - 2012-12

Between the completion of my Master's and Doctoral degrees in Astrophysics, I worked on a variety of scientific and technical tasks in support of the NASA Chandra mission, on the Science Data Systems team at NASA's Chandra X-ray Center. Here, I fulfilled the following roles:

  • X-­ray Astronomer: Conducted spatial and spectral analysis of galaxies in Chandra and XMM­-Newton X­-ray imaging observations.
  • X-ray Data Specialist : Contributed to software development and testing of the Chandra Interactive Analysis of Observations (CIAO) imaging, spectroscopic, and timing analysis software, in the form of Python scientific data analysis scripts.
  • Served as primary writer of the scientific web documentation for the Chandra X-ray Center (CXC) Chandra Source Catalog (CSC), CXC Sherpa spectralfitting package, and the Virtual Astronomical Observatory (VAO) Iris SED analysis tool.
  • Awards for this work:
    • NASA Public Service Group Achievement Award
    • Smithsonian Cash Award
Education

Ph.D. Physics

McGill University
2013 - 2017

Master of Arts Astronomy

Boston University
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Bachelor of Arts Physics

University of Pennsylvania
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