Energy Systems Modeling Intern (Python, NumPy)

Remote · Part-time (15-20 hrs/week) · San Francisco Bay Area, CA · Unpaid / Academic CreditWhat You're Walking IntoKelvolta builds physical models of how large electrical loads actually behave, at timescales ordinary metering never sees. Our work spans industrial manufacturing, AI data centers, EV charging, and other markets in which demand is growing fast and the economics of storage turn on behavior nobody has measured. We're a lean team, so interns work close to the physics rather than on the edges of it."…Learning to build things that actually matter in a startup where I'm constantly learning and adapting." — L. Sanchez, UC Santa BarbaraSkills You'll Put to Use and DevelopNumerical modeling in Python with NumPy and SciPy: building a defensible simulation of a physical system from published equipment specifications rather than from a ready-made datasetTime-series and frequency-domain analysis: sampling, filtering, and what a measurement at one resolution can and cannot tell you about behavior at anotherParameter discipline: every input in our models is sourced and documented, so that any assumption can be checked or replaced by someone who disagrees with itTranslating manufacturer datasheets and technical literature into model parametersWho We're Looking ForCurrently-enrolled (not graduated) upper-division undergraduate or graduate students in Physics, Electrical Engineering, Applied Mathematics, or a related quantitative field. We're looking for people who can code but whose instinct is to ask what the system is physically doing, not just what the data says.Useful background in any combination: Python with NumPy/SciPy, signal processing, power electronics or circuits coursework, MATLAB or Simulink, numerical methods, control systems.If you have ever built a model of something you could not directly measure, say so in your application.Past interns have come in with strong fundamentals and left with experience building production-level work. We care more about what you can do than what year you're in.What You GetHands-on experience working on real projects with meaningful impactOpportunities to take ownership and contribute to production-level workDirect mentorship from a domain-expert team, including a CEO with 25 years of energy project development experienceExposure to real datasets and practical problem-solvingA fast-paced environment that helps you grow quicklyA strong portfolio of work you can speak to in interviewsEligibility for academic credit (8–10 units, subject to university approval)Priority consideration for extended or paid opportunities based on performanceThis is an unpaid internship. All participants are eligible for academic credit, and strong performers are considered for paid roles.LogisticsCommitment: 15-20 hours per weekDuration: Minimum 10 weeksStart and end dates: Flexible; prefer November start dateFormat: Remote · Part-time · UnpaidInterviews: Candidates should be available for a ~15-minute initial interview the week of November 9. Please apply only if you can schedule that conversation.How to ApplyClick Easy Apply above. Candidates who interview the week of November 9 strongly preferred. Applications reviewed on a rolling basis.#Physics #ElectricalEngineering #SignalProcessing #NumPy #SciPy #ComputationalPhysics #PowerSystems #IndustrialEnergy #DataCenters #AIInfrastructure #EnergyTech #Simulation #Python #Internship #StartupInternship