Computational Modeling and Data Analysis for X-ray Astrophysics

ORAU; Greenbelt (MD); On-site; USD 70,000 - 120,000; Full time

Job summary

ORAU, in collaboration with NASA, is seeking a researcher specialized in astrophysics to model black holes and their environments. The role involves developing advanced statistical methods and machine-learning algorithms to analyze high-energy X-ray data.

Candidates must hold a Doctoral Degree and demonstrate expertise in spectral fitting and data interpretation techniques. The position requires a commitment to high-impact astrophysical research in Greenbelt, Maryland.

Qualifications

• Expertise in astrophysics with a focus on black holes and their environments.
• Strong background in modeling X-ray interactions with gas near compact objects.
• Proficient in various statistical and machine-learning techniques for data analysis.

Responsibilities

• Develop and implement models for interpreting observational data of black holes.
• Conduct spectral fitting and Bayesian inference techniques.
• Measure black hole spins using advanced spectroscopy methods.

Skills

Statistical techniques

Machine-learning algorithms

Spectral fitting

Radiative transfer

High-resolution spectroscopy

Education

Doctoral Degree

Job description

Organization

National Aeronautics and Space Administration (NASA)

Reference Code

0280-NPP-NOV26-GSFC-Astrophys

Job Description

The conditions near accreting compact objects are very extreme, creating environments which are difficult to replicate in laboratories on Earth. This includes objects such as neutron stars or stellar‑mass black holes in binary systems, or supermassive black holes in the active centers of most galaxies, from which large quantities of high‑energy radiation are produced. Most of this radiation can be observed in the X‑ray band. By modeling the interaction of these X‑rays with the gas near the black hole, and how this radiation will be affected after the interaction, it is possible to infer the key physical properties of both compact objects and the surrounding material. Specifically, combining the models with X‑ray observations, we can obtain information about the black hole – for example whether it is spinning or not and how fast, as well as information regarding the gas nearby, such as its composition, temperature, and dynamics. The accuracy of these models requires collection and curation of atomic parameters, numerical methods for radiative transfer, and detailed calculations of ionization and energy balance. Implementation of these models to interpret observational data requires specialized statistical techniques such as spectral fitting and Bayesian inference. We are actively working on developing and implementing all these tools in a variety of astrophysical problems, which include: measuring black hole spins using reflection spectroscopy; studies of disk‑jet‑corona connection in accreting sources using spectral‑timing techniques (X‑ray lags, power‑spectra analysis, etc.); photoionization modeling of astrophysical plasmas at high‑densities; development of advanced spectral‑fitting techniques using machine‑learning algorithms; and other emerging directions. Importantly, high‑resolution spectroscopy, timing analysis, and polarization modeling are currently the foremost aspects in modeling efforts for the next decade.

Field of Science

Astrophysics

Advisors

Javier Garcia Martinez
[e-mail]

Eligibility Requirements

• U.S. Citizens
• U.S. Lawful Permanent Residents (LPR)
• Foreign Nationals eligible for an Exchange Visitor J‑1 visa status
• Applicants for LPR, asylees, or refugees in the U.S. at the time of application with a valid EAD card and I-485 or I-589 forms in pending status
• Degree: Doctoral Degree

Comments

Applications from citizens of Designated Countries will not be accepted at this time, unless they are Legal Permanent Residents of the United States.