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Internship Stochastic Modeling Jobs in California

... the ML model is the only stochastic component. We iterate fast (multiple robot generations in ... with strong project or internship experience are welcome to apply) * Strong programming ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

Internship Stochastic Modeling information

What do internship stochastic modeling positions do?

As an intern in stochastic modeling, you will typically work on projects involving data analysis, model development, and simulation of random processes. Your daily tasks may include cleaning and organizing datasets, implementing mathematical models using programming languages like Python or R, and running simulations to test hypotheses. You will likely collaborate with senior modelers and data scientists, participate in team meetings, and may also present your findings. This role offers exposure to real-world applications in industries such as finance, insurance, or engineering, helping you develop both technical and communication skills.

What is the difference between Internship Stochastic Modeling vs Data Analyst?

AspectInternship Stochastic ModelingData Analyst
Required CredentialsRelevant coursework, basic programming skillsBachelor's in statistics, data science, or related field
Work EnvironmentInternship setting, research-focused, financial or tech industriesOffice environment, various industries including finance, marketing, healthcare
Employer & Industry UsageFinancial firms, tech companies, research institutionsCorporations, consulting firms, government agencies

Internship Stochastic Modeling typically involves applying probability and statistical techniques to model uncertainty, often in finance or research settings. Data Analysts focus on interpreting data, creating reports, and supporting decision-making across diverse industries. While both roles require analytical skills, stochastic modeling internships emphasize mathematical modeling, whereas data analyst roles focus on data manipulation and visualization.

What is an internship stochastic modeling?

Internship Stochastic Modeling positions are temporary roles designed for students or recent graduates to gain practical experience in applying stochastic processes and mathematical modeling techniques. Interns typically work under the guidance of experienced professionals in fields such as finance, insurance, engineering, or data science. They assist with analyzing data, developing models that incorporate randomness or uncertainty, and supporting decision-making processes. These internships provide valuable hands-on experience and help interns build skills in programming, statistical analysis, and problem-solving relevant to stochastic modeling careers.

What are the key skills and qualifications needed to thrive as an internship stochastic modeling?

To thrive in a Stochastic Modeling Internship, you need a solid background in probability, statistics, and mathematics, often supported by coursework or a degree in a quantitative field. Familiarity with programming languages such as Python, R, or MATLAB, and experience using statistical modeling software are typically expected. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and explaining complex concepts. These abilities ensure you can develop accurate models, collaborate with teams, and contribute valuable insights to data-driven decision-making processes.

What are the most commonly searched types of Stochastic Modeling jobs in California?

The most popular types of Stochastic Modeling jobs in California are:

What job categories do people searching Internship Stochastic Modeling jobs in California look for?

The top searched job categories for Internship Stochastic Modeling jobs in California are:

What cities in California are hiring for Internship Stochastic Modeling jobs?

Cities in California with the most Internship Stochastic Modeling job openings:

2026 PhD Residency - Non-Linear Physical Dynamics & Device Characterization (Future of Compute)

X, the moonshot factory

Mountain View, CA • On-site

$100K - $147K/yr

Full-time

Re-posted 12 days ago


Job description

2 0 2 6 P h D R e s i d e n c y - N o n - L i n e a r P h y s i c a l D y n a m i c s & D e v i c e C h a r a c t e r i z a t i o n ( F u t u r e o f C o m p u t e )
Internship Mountain View, CA
Project Goal:This is the flagship moonshot for 'The Future of Compute' at X (the Moonshot Factory). Our objective is to move away from the traditional paradigm of simulating physics on digital chips. Instead, we are building physical machines whose intrinsic dynamics ARE the computation itself, achieving a 1,000,000x improvement in useful compute per Joule.
This residency focuses on the raw physics of non-linear computing. By studying how nanoscale devices behave, synchronize, and drift in a laboratory environment, you will extract the physical laws that make our substrate inherently superior to passive systems. You will study how to harness non-linear dynamics and physical noise to build stable, room-temperature probabilistic computers, bridging microscopic device physics with high-level circuit design.
How you will make 10x impact:
  • Collaborate on the physical modeling and physical characterization of nanoscale devices (e.g., RRAM, carbon nanotube FETs, and phase-locked micro-oscillators), focusing on mapping their non-linear phase-locking dynamics and non-equilibrium thermodynamics.
  • Independently design and execute laboratory testing routines to characterize device-level non-linear activation functions, evaluating their suitability for physical neural network computation.
  • Perform high-resolution noise-spectroscopy and time-domain measurements to analyze 1/f noise, thermal fluctuations, and resistance drift under long-term continuous operation.
  • Analyze and model how ambient physical noise and stochastic thermal fluctuations can be harnessed as a computational resource for probabilistic computing (p-bits) and optimization, rather than suppressed.
  • Investigate the physical coupling and synchronization dynamics of small arrays of physical oscillators, characterizing the limits of multi-phase locking and synchronization stability.
  • Develop compact device behavioral models (e.g., Verilog-A, analytical Python equations) derived directly from physical measurements to update our circuit and system-level simulators.

This project aims to push the limits of science and modeling as we know them and to prove how ML can radically accelerate our understanding of the world
  • Location: X's headquarters in Mountain View, CA
  • Start Date(s): Year-round rolling basis
  • Duration: a flexible 4 mo. to 1 year program based on project team needs and your availability

Throughout your AI Residency you can expect:
  • To be embedded in an agile, confidential project team focused on physical exploration, challenging existing assumptions about noise, stability, and digital over-engineering.
  • Direct mentorship from experimental device physicists, materials scientists, and advanced measurement engineers.
  • Access to state-of-the-art semiconductor characterization labs and device probing equipment.

What you should have:
  • Currently enrolled in a PhD program in Physics, Applied Physics, Materials Science, Electrical Engineering (solid-state electronics focus), or a related STEM field.
  • Strong hands-on experience in the physical and electrical characterization of nanoscale devices (such as memristors/RRAM, nanoscale oscillators, or 2D materials) in a laboratory environment.
  • Proficiency in scripting automated measurements (Python/PyVISA, LabVIEW) and analyzing complex physical and time-series datasets.
  • Deep theoretical understanding of solid-state device physics, charge transport, noise processes, and non-equilibrium statistical mechanics.
  • Ability to translate physical device behavior into analytical, numerical, or compact models (e.g., Python, MATLAB, COMSOL, or Verilog-A).

It'd be great if you also had these:
  • Prior experience characterizing phase-locked coupled-oscillator networks, RF micro-oscillators, or stochastic/probabilistic circuits (p-bits).
  • Familiarity with carbon nanotube electronics, novel non-volatile memories, or advanced atomic-force microscopy (AFM/conductive-AFM).

Additional public information :
https://www.wired.com/video/watch/astro-teller-captain-of-moonshots-at-x-speaks-at-wired25
https://www.bloomberg.com/news/videos/2019-10-10/alphabet-x-s-astro-teller-on-bloomberg-studio-1-0-video
The US base salary range for this position is $100,000 - $147,000 + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.
An Equal Opportunity Workplace
At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you have a disability or special need that requires accommodation, please contact us at x-accommodation-request@x.team .