Adaptive FaML (facet-attached microlens) workflow for rapid microlens prototyping - BC-1042
Project type: ResearchDesired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences, Mathematics, Physics / Astronomy, Natural Sciences
Company: Dream Photonics Inc.
Project Length: 6 months to 1 year
Preferred start date: 01/01/2027
Language requirement: English
Location(s): Vancouver, BC, Canada
No. of positions: 2
Desired education level: CollegeUndergraduate/BachelorMaster'sPhDPostdoctoral fellowRecent graduate
Open to applicants registered at an institution outside of Canada: No
About the company:
Dream Photonics is a Vancouver-based photonics company solving one of the biggest bottlenecks in artificial intelligence data centers: getting light into and out of computer chips fast enough, cheaply enough, and at high enough volume to keep pace with AI's growth. The company has invented a way to 3D-print microscopic, custom lenses that automatically correct for laser-to-chip misalignment, turning a slow, manual, one-at-a-time optical packaging process into a fast, automated one. The same core technology also applies to quantum computing, quantum communication, and defence sensing, where Dream's adaptive optics can couple quantum-dot lasers and single-photon sources with very low loss. Dream is building a national talent pipeline with Canadian universities to help solve the field's two biggest remaining challenges: reducing optical loss and scaling manufacturing from prototype to mass production.
Describe the project.:
This project asks researchers to build an automated, repeatable workflow for rapid microlens prototyping in laser-to-photonic-integrated-circuit (PIC) hybrid integration. Dream Photonics has developed 3D-printed, adaptive micro-lenses ('Facet-Attached Microlenses,' or FaML) that correct for real-world placement error between a laser and a chip, replacing slow, mechanically precise active alignment with a fast, software-defined 'place and print' process. The researcher will combine CAD/optical-simulation tools, Python-based automation, and reliability/repeatability testing to develop a workflow that takes a given laser-chip pairing from design through fabrication to validated performance — culminating in a product-focused tool that meets industry standards for a chosen fabrication platform and process. This work builds directly on Dream's peer-reviewed results (Mitchell et al., 'Low Loss Optical Coupling to Photonic Integrated Circuits via Adaptive-Facet-Attached Microlenses,' OFC 2026). Researchers will have access to Dream's 3D micro-printing and metrology equipment, in-house optical and electrical test infrastructure, and mentorship from the company's engineering team, working alongside PhD researchers and R&D staff on real production tooling. The role offers hands-on experience spanning micro-optics design, hybrid integration, and reliability engineering — skills directly transferable to AI data-center interconnects, quantum photonics, and defence/microwave-photonics applications.
Required expertise/skills:
Optical/photonic design and simulation (e.g., Zemax, Lumerical, or similar CAD/simulation tools); hands-on experience with laser-to-chip or fibre-to-chip coupling and hybrid integration; Python-based automation and data analysis; familiarity with cleanroom micro/nanofabrication processes; experience with reliability and repeatability testing of optical/photonic assemblies. Prior exposure to 3D micro-printing, two-photon polymerization, or adaptive optics is an asset but not required.
