Semiconductor EDA Intern (Remote)

Work Type: Internship

Julia Computing is looking for interns with an interest in improving the state of the art of EDA tooling by contributing to the development of JuliaSPICE, JuliaSim and related products. Various projects may be available depending applicant background and interest. 

Julia Computing's mission is to develop products that bring Julia's superpowers to its customers. Julia Computing's flagship product is JuliaHub, a secure, cloud based, software-as-a-service platform for developing Julia programs, deploying them, and scaling to thousands of nodes. Julia Computing was founded in 2015 by the creators of the Julia programming language for artificial intelligence, machine learning, analytics, data science, modeling, and simulation.

Applicants should include a cover letter detailing their relevant previous experience. Cover Letters are required. Applications with missing cover letters may be rejected without review. Relevant experience, e.g. GUI, compiler development or machine learning without direct modeling and simulation application is acceptable for internships. Please also highlight any relevant coursework or other experience in numerical methods, modeling and simulation or compiler development. Lastly, please include any programming experience in Julia.

Cover letters should include dates of availability (e.g. semester or summer, part time vs full time, etc.). Julia Computing internships can have flexible start dates and duration, depending on applicant interest. Applications are currently open for start dates through Summer 2022. For students in PhD programs where supervisor approval is required for internships, please include whether such approval has been obtained. Supervisor approval is not required for initial applications, but must be obtained before offers can be made.

Julia Computing internships are remote by default, but may be onsite at our Boston office.

Potential Projects Include

  • Semiconductor Modeling (Compact Models or TCAD)
  • GUI development
  • Compiler Development (E.g. structural optimzation of differential equations, auto-parallelization, etc.)
  • Simulator Frontend Development (e.g. SPICE, KiCAD, etc. file format parsers)
  • Machine learning techniques for accelerated simulation

Suggested Applicant Background

  • A bachelor's or master's degree in mathematics, computer science, physics, electrical engineering or a related technical discipline. In progress degrees are acceptable for internships.
  • Strong programming experience (Julia preferred, but not required)
  • Demonstrated capabilities or coursework relevant to a particular potential project area (please highlight in cover letter)
  • Experience with numerical methods or simulation
  • Experience with electronic circuit simulation 

Above listed background is advisory only. Applications by non-traditional applicants that believe they have relevant background and experience (e.g. through open source work), but do not fit the above background are encouraged.  

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