INDUSTRY · ACADEMIC · TALENT

Three ways to work with us.

How to work with IPNL — engagement structures, time horizons, and how to start a conversation.

For industry

The lab structures industry engagements in three layers, by depth of commitment.

Layer 1 · framework partnership

Multi-year framework

24–36 month research agreements with named deliverables, joint personnel, and milestone reviews. This is how the Huawei, OPPO, AIROHA, and MediaTek engagements are run.

Layer 2 · funded research project

Scoped research project

12–24 month single-scope projects with a defined research question and contracted hours. Examples: Google Research Award (US$40k, 2024); ITF-ITSP (HK$801k, 2024).

Layer 3 · consultancy / advisory

Time-bounded advisory

A few weeks to a few months: integrity-monitoring frameworks, architecture review, technical due diligence, expert opinion. SAIC Motor runs in this mode.

Time horizons

Fast lane · can start quickly
  • Evaluate your algorithm on UrbanNav
  • Technical Q&A call (30–60 min)
  • Review a paper draft or proposal
  • Invited talk on existing topics
Slow lane · needs setup
  • Joint data collection campaign
  • Co-supervised PhD student
  • Multi-year framework partnership
  • Custom dataset for your city

How to start

Send a message → with:

  • Who you are and your affiliation
  • The nature of the collaboration and which layer above it fits
  • Constraints — timing, location/timezone, budget if relevant
  • Links to relevant material (technical brief, RFP, prior work)

See also: R&D Projects for a partner-by-partner view of how existing collaborations are structured.

For academic collaborators

Joint publications and co-authored papers; dataset sharing and benchmark development; co-advised students (PhD, MPhil, visiting); joint grant proposals; workshop and conference co-organization. The lab co-chairs the ION/IAG Working Group on Positioning at Asian Urban Canyons and welcomes collaborators on the working-group track.

Particular openings in 2026 include cross-institutional projects with Taiwan partners, integrity-monitoring methodology exchanges, and joint dataset campaigns for new cities.

To propose academic collaboration, send a message → with a brief description of the proposed work and any timing constraints.

For students, postdocs, and research assistants

PhD students

Strong quantitative background in GNSS, signal processing, robotics, or machine learning. Self-directed, comfortable with field experiments, eager to publish in top venues.

Postdoctoral fellows

Track record of high-quality publications in positioning, navigation, or related areas. Interest in mentoring students and leading independent research threads.

Visiting researchers

PhD students or early-career researchers from partner institutions interested in 3- to 12-month research visits.

Research assistants

Engineering graduates interested in hands-on dataset collection, system integration, and algorithm development.

Current interests (2026)

  • Urban GNSS benchmarking — new cities, new sensors, new challenges
  • Integrity monitoring — safety-critical applications and certification pathways
  • Factor graph optimization — alternative fusion architectures to EKF
  • Embodied AI localization — drones, robots, delivery vehicles
  • Taiwan partnerships — joint projects and student exchanges

How to apply

Send a message → with:

  • Who you are (name, affiliation, role)
  • What you want to do (1–2 sentences)
  • Why you think IPNL is a good fit
  • Your CV and relevant publications
  • Timeline and constraints

For PhD applications, please also mention your funding situation (self-funded, seeking fellowship, etc.) and your preferred start date.

Send us a message

Tell us briefly who you are and what you’d like to do.

Email:

Office: Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.

Profiles: PolyU Staff Profile · PolyU Scholars Hub · Google Scholar · ORCID · LinkedIn · GitHub (personal) · GitHub (IPNL).