Best Fit
Your research code is stronger than it looks on a resume. Let's fix that.
Years of research code. No engineering title yet.
You have a degree, maybe several, in physics, mathematics, chemistry, biology, statistics, or a related field. You've been writing serious code for years: Python pipelines, statistical models, simulations, numerical methods. Your work contributed to real research. But software engineering teams see your background and route you to the wrong pile. You're not missing technical ability. You're missing a positioning bridge.
STEM researchers consistently outperform in technical interviews. When they get invited to one.
Challenges we help solve
- Research code is dismissed as 'scripting,' not engineering
- PhD creates seniority expectations with no industry experience to match them
- No software engineering title despite years of production-grade coding
- Hard to translate research background into engineering portfolio language
What you leave with
- Internship experience in a real engineering org that anchors your resume
- A mentor who bridges research-to-engineering and fills the practical gaps
- Career coaching that turns your quantitative depth into a genuine differentiator
- A portfolio that reads as software engineering, not just academic research
The hiring filter doesn't know what to do with you, so it routes you wrong.
Software engineering teams see 'physics PhD' or 'research scientist' and assume you want a research role. They're not wrong that your background is strong. They just don't have a mental model for where you fit. That's a positioning problem, not a skills problem.
- Research code isn't recognized as 'engineering experience' by screeners
- Advanced degrees create awkward seniority expectations for entry-level roles
- Your technical depth gets overlooked because your job titles don't match
Application Review
Dr. Priya S. · Physics PhD, 4 years research coding
From the resume
PhD, Computational Physics
Simulation modeling, numerical methods, C++ and Python
Graduate Research Assistant
3 years writing and maintaining simulation pipelines
Published: Phys. Rev. Letters
Data analysis and visualization toolchain
GitHub: 14 repos
Monte Carlo, HPC scripts, custom analysis libraries
Recruiter read
"Strong research background. Forwarding to our research scientist pipeline instead."
Applied to: Software Engineer (Backend) · Routed to: Research Scientist
Your quantitative background is a genuine engineering advantage, when it's properly framed.
You already have systems thinking, rigor, and real coding experience. We help you reframe your background in engineering terms, add internship experience that provides professional context, and build a job search strategy around companies that actually value what you bring.
- Internship work translates research skills into engineering portfolio language
- Technical mentorship fills the team collaboration and workflow gaps
- Coaching that positions your STEM background as a domain advantage in tech
What Your Background Actually Means
Dr. Priya S. · Computational Physics → SWE
Simulation pipelines in Python
Systems programming + data pipeline engineering
Statistical modeling & analysis
Applied ML / data-intensive backend
HPC scripting & job scheduling
Distributed systems & infrastructure basics
Reproducible research environments
Containerization & environment management
Collaborating on shared codebases
Version control & team engineering norms
Sound like you? Let's talk.
The admissions project is how we get to know you. Build something real and show us what you've got.
Frequently asked questions
Common questions from stem academics considering the program.
- Does my specific field matter - physics vs. biology vs. statistics?
- Less than you'd think. What matters is that you can code, think rigorously, and are ready to work in an engineering team environment. The field shapes where you might be most competitive (biotech, fintech, climate tech), but we work with STEM backgrounds across disciplines.
- I have a PhD. Will employers think I'm overqualified?
- Some will, and that's real. But plenty won't, especially at startups and technical companies where research depth is genuinely valued. Part of what we do is help you find and target the right employers, not just push your resume toward the wrong ones.
- My research code is messy, not production quality. Is that a problem?
- It's expected. Research code and production code are different, and we know that. The internship experience gives you the production context; the mentorship helps you understand the norms. You don't need to arrive with perfect code.