# David Osterman

> Cryogenic Engineer | Scientist

Location: New York City Metropolitan Area, United States
Profile: https://flows.cv/davidosterman

PhD physicist with a passion for all things science and a strong aptitude for communicating technical concepts to both technical and non-technical people. At Bluefors, I help provide laboratories across the country with cryogenic solutions to enable advancements in quantum computing and other low-temperature research.


Skills

Cryogenics: dilution refrigerators, superconducting materials, SQUIDs, transition edge sensors, liquid noble cryogenics

Hardware: dilution refrigerator, cryogenic nanopositioning stages, fiber-optics, free-space lasers, ultra-high vacuum systems, high pressure plumbing, radioactive sources

Quantum Computing: RF components, superconducting aluminum films, quasiparticle diffusion

Modeling/Simulation Software: SOLIDWORKS, L-Edit, COMSOL, Onshape, KLayout

Languages & Platforms: python, SQL, C, C++, git, bash, Linux 

Python Libraries: numpy, pandas, PyTorch, sklearn, tensorflow, NLTK, seaborn, matplotlib

Machine Learning: NLP, deep learning, CNNs, Reinforcement Learning, Markov processes, Thompson sampling, UCB, data collection and cleaning, regression, classification, clustering, error analysis, API

Quantitative: stochastic optimization, statistical analysis, data visualization, data pipelines

Soft Skills: leadership, project management, communication skills, time management, flexibility

Certifications:  The Erdős Institute Deep Learning Boot Camp

## Work Experience
### Cryogenic Engineer | Scientist @ Bluefors
Jan 2025 – Present | New York City Metropolitan Area

### SCGSR Fellow/CNM User @ Argonne National Laboratory
Jan 2021 – Jan 2024 | Lemont, Illinois, United States
Department of Energy Office of Science Graduate Student Research (SCGSR) Program Fellow, performing experimental dark matter physics research for the SPICE/HeRALD Collaboration.

-Built and upgraded data acquisition system to be fully automated - which reduced required
manpower to one person - and fully remote - which reduced active time spent by 90%.
-Employed causal inference and predictive models and verified the effectiveness of a
potential strategy for the collaboration.
-Designed first instrumented superconducting IrPt bilayer Transition Edge Sensor (TES)
device chips and measured first instances of quasiparticle diffusion in superconducting
aluminum fins attached to an IrPt TES.

### Research Assistant @ University of Massachusetts Amherst Physics Department
Jan 2021 – Jan 2024 | Amherst, Massachusetts, United States
Performed experimental dark matter physics research for the SPICE/HeRALD collaboration

-Performed time series and event-based analysis, which contributed to multiple papers,
including a world-leading physics publication (currently in-preparation).
-Constructed pipelines in Python for processing raw data. Employed causal inference and
predictive models, which uncovered a 150% to 350% increase in device performance.
-Coordinated and led dilution refrigerator runs and maintenance.

### Research Assistant @ Brown University Department of Physics
Jan 2016 – Jan 2021 | Providence, Rhode Island, United States
Research assistant performing cryogenic and biophysics research.

-Created the code basis (in C) of time series data digitization for the lab. Performed multivariate event ordering.
-Designed and ran tests verifying the effectiveness of critical sub-processes of the main data acquisition device in the lab.
-Studied and modeled the Brownian motion of stochastic particles.


## Education
### Doctor of Philosophy - PhD in Physics
University of Massachusetts Amherst

### Master of Science - MS in Physics
Brown University

### Bachelor's degree in Physics
Rutgers University–New Brunswick


## Contact & Social
- LinkedIn: https://linkedin.com/in/dzosterman

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Source: https://flows.cv/davidosterman
JSON Resume: https://flows.cv/davidosterman/resume.json
Last updated: 2026-04-13