Large-Scale Integrated Photonics Lab Research Associate Intern

The Large-Scale Integrated Photonics Lab and the Emerging Accelerators Group at Hewlett Packard Labs are seeking highly motivated summer interns to contribute to the development of breakthrough technologies for the next generation of computing systems.

Successful candidates will work alongside world-class researchers advancing innovations in integrated photonics, AI hardware accelerators, in-memory computing, advanced semiconductor devices, and novel computing architectures. Research projects span the full technology stack, from devices and circuits to systems and applications, with the goal of enabling future computing platforms that deliver significant improvements in performance, energy efficiency, scalability, and sustainability.

Interns will have the opportunity to participate in cutting-edge research involving silicon photonics, photonic interconnects, CMOS and mixed-signal circuits, emerging memory technologies, AI accelerators, optical computing, and heterogeneous computing architectures. Depending on their background and interests, interns may contribute to the design, simulation, fabrication, testing, characterization, and evaluation of novel hardware and system concepts.

Responsibilities:

• Conduct innovative research in integrated photonics, emerging electronics, and next-generation computing architectures.
• Design, model, and evaluate photonic, electronic, and electro-optic devices and systems.
• Develop CMOS, mixed-signal, and hardware accelerator circuits for advanced computing applications.
• Participate in the development of in-memory computing and AI acceleration technologies.
• Perform experimental characterization and testing of photonic and electronic devices.
• Develop software tools, simulation frameworks, and machine learning workflows to analyze and optimize hardware systems.
• Collaborate with multidisciplinary teams of researchers, engineers, and scientists.
• Present technical findings through reports, presentations, and publications.

Education & Experience:

• Currently pursuing a PhD degree in Eletrical Engineering, Computer Engineering, Computer Science, Physics, Photonics, Materials Science, or a related technical field.

• Experience in one or more of the following areas:
  • Integrated photonics and silicon photonics
  • CMOS, analog, mixed-signal, or RF circuit design
  • Computer architecture and hardware design
  • FPGA, ASIC, or accelerator development
  • In-memory computing and emerging memory technologies
  • Optical communications and photonic systems
  • Semiconductor device physics
  • Machine learning systems and AI hardware
  • Modeling and simulation of electronic or photonic systems
• Familiarity with relevant tools and environments such as:
  • Cadence, Synopsys, Keysight ADS, or similar EDA platforms
  • MATLAB, Python, C/C++, SystemVerilog, Verilog, VHDL, or related languages
  • Machine learning frameworks such as PyTorch or TensorFlow
  • Electronic and photonic test and measurement equipment
• Strong analytical, problem-solving, and experimental skills.
• Excellent written and verbal communication abilities.

• Experience with laboratory experimentation and device characterization.
• Experience in photonic integrated circuits, optical communications, or semiconductor fabrication.
• Experience developing hardware accelerators for AI, machine learning, or data-intensive applications.
• Demonstrated ability to work effectively in collaborative research environments.

• →Hands-on experience developing technologies that could shape future computing platforms.
• →Exposure to interdisciplinary research spanning devices, circuits, architectures, systems, and applications.
• →Mentorship from leading researchers in photonics, computer architecture, and advanced hardware systems.
• →Opportunities to contribute to publications, patents, and technology demonstrations.
• →Experience working in a world-class industrial research environment focused on translating breakthrough ideas into real-world impact.

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Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.

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