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Hire Ethan V.

United States

USD 12 /hr

Freelance Physicist & Data Analyst | Expertise in Python, Academic Writing, & data analysis/visualization

Profile Summary

I am an astrophysics researcher with a strong background in observational astronomy, cosmology, and computational modeling. I hold a B.S. in Physics and Astronomy with a minor in Mathematics from the University of Rochester (cum laude, Math/Physics GPA: 3.96/4.00) and will begin my Ph.D. in Physics at Johns Hopkins University in 2026, specializing in cosmology. My research spans stellar population synthesis, large-scale structure, and galactic dynamics. At the Harvard-Smithsonian Center for Astrophysics, I developed the first high-resolution simple stellar population (SSP) library optimized for JWST, incorporating multiple stellar atmosphere models and advanced telluric correction techniques. This work, validated on JWST and WAGGS data, significantly improved spectral fits and was presented at the AAS 246 meeting. At the University of Rochester, I created a novel statistical framework for constraining primordial non-Gaussianity using higher-order moments of the density field, achieving ~21% improved sensitivity over the two-point correlation function. I have also led projects at the Leibniz Institute for Astrophysics Potsdam, using Gaia DR3 and simulations to revise estimates of the Milky Way bar’s structure, and at Los Alamos National Laboratory, applying Bayesian Monte Carlo methods to fit high-dimensional hydrodynamic model parameters. My technical skills include Python, Bayesian inference, MCMC, spectral fitting (pPXF), large-scale data analysis, and high-performance computing. I have observational experience on the 6.5 m Magellan telescope in Chile and extensive experience working with survey data from DESI, Gaia, and JWST. Beyond research, I have served as a graduate course evaluator, undergraduate teaching intern, and physics tutor, as well as a mentor for undergraduate students. I have authored multiple peer-reviewed papers and presented at international conferences, demonstrating strong communication skills and project leadership.

Subject Matter Expertise

• ★ Bayesian Statistics
• ★ Astrophysics
• ★ Python
• ☆ Statistics
• ☆ Applied Statistics
• ☆ Regression Analysis
• ☆ Multivariate Analysis
• ☆ Nonlinear Regression
• ☆ Quantum Statistics
• ☆ Earth & Atmospheric Science
• ☆ Theoretical Physics
• ☆ Computational Physics
• ☆ Applied Physics
• ☆ Astronomy
• ☆ Solar Physics
• ☆ Cosmology
• ☆ Applied Mathematics
• ☆ Mathematical Models
• ☆ Computational Sciences
• ☆ Differential Equations
• ☆ Pure Mathematics
• ☆ Calculus
• ☆ Geometry
• ☆ Discrete Mathematics
• ☆ Integral Equations

Services

• Writing
• Research
• Data & AI

Writing Technical Writing, General Proofreading & Editing

Research Scientific and Technical Research, Systematic Literature Review, Secondary Data Collection

Data & AI Data Visualization, Big Data Analytics, Data Processing, Data Insights

Work Experience

Researcher

University of Rochester

August 2023 - Present

Research Intern

Leibniz Institute for Astrophysics Potsdam

May 2022 - Present

Research Fellow

Center for Astrophysics Harvard & Smithsonian

September 2024 - August 2025

Workshop Fellow

Los Alamos National Laboratory

June 2023 - August 2023

Education

Ph.D. (Physics)

Johns Hopkins University

July 2025 - Present

Physics and Astronomy, B.S. (Physics and Astronomy)

University of Rochester

August 2020 - May 2024

(Physics)

University of Sydney

February 2023 - June 2023

Certifications

• Certification details not provided.

Publications

JOURNAL ARTICLE

E Vislosky, Ivan Minchev, S Khoperskov, M Martig, Tobias Buck, T Hilmi, Bridget Ratcliffe, J Bland-Hawthorn, Alice Quillen, M Steinmetz, et al. (2024). Gaia< DR3 data consistent with a short bar connected to a spiral arm . Monthly Notices of the Royal Astronomical Society.

REPORT

Modeling Dynamic Behavior of Stainless Steel (SS304L) [Slides] @article{osti_1995121, title = {Modeling Dynamic Behavior of Stainless Steel (SS304L) [Slides]}, author = {Vislosky, Ethan Langford and Baker, James Andrew Jr. and Nguyen, Thao Thi Tam and Plohr, JeeYeon Nam}, abstractNote = {Abstract not provided.}, doi = {10.2172/1995121}, url = {https://www.osti.gov/biblio/1995121}, journal = {}, number = , volume = , place = {United States}, year = {2023}, month = {8} } . Los Alamos National Laboratory.