HPE Labs

HPE Labs - Research Engineer III

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description: About the Role

The Large‑Scale Integrated Photonics (LSIP) Lab at Hewlett Packard Labs is seeking an exceptional Research Scientist / Research Engineer to contribute to groundbreaking research in neuromorphic and photonic computing. As part of HPE Belgium’s participation in leading European research initiatives, you will play a key role in developing next‑generation optical spiking neural networks and neuromorphic computing systems targeting challenging applications including radar signal processing, optical communications, high‑energy physics, and medical imaging. This is a unique opportunity to work at the intersection of integrated photonics, machine learning, neuromorphic computing, and advanced hardware systems within a world‑class multidisciplinary research team.

What You’ll Do

• Contribute to externally funded research programs focused on optical and neuromorphic computing technologies.
• Design, develop, and evaluate next‑generation photonic and hybrid photonic‑electronic computing architectures.
• Research and develop optical spiking neural network concepts, neuromorphic algorithms, and event‑driven computing approaches.
• Identify high‑impact application domains where neuromorphic and photonic computing can address critical computational bottlenecks.
• Translate advanced scientific concepts into demonstrators, prototypes, and proof‑of‑concept systems.
• Collaborate closely with experts in photonics, electronics, machine learning, software engineering, and systems research.
• Publish research findings in leading scientific conferences and journals.
• Contribute to project deliverables, technical reports, and presentations for European research consortia and stakeholders.
• Develop software tools, simulations, and data analysis workflows, primarily in Python.

Areas of Focus

• Integrated photonic devices and systems
• Optical neural and spiking network architectures
• Neuromorphic algorithms and event‑driven AI
• Hardware‑software co‑design
• Photonic computing platforms and accelerators
• Application‑driven research and technology demonstrations

What We’re Looking For

Required Qualifications

• PhD in Photonics, Electrical Engineering, Physics, Computer Engineering, Computer Science, or a closely related discipline.
• Strong expertise in one or more of the following areas: Integrated Photonics, Photonic Systems, Photonic Computing, Neuromorphic Computing, Spiking Neural Networks, Event‑Driven Computing.
• Outstanding publication record in peer‑reviewed journals and conferences relevant to the field.
• Ability to contribute across multiple stages of the research process, including theory, modeling, system design, experimentation, validation, and application development.
• Strong Python programming skills.
• Excellent written, verbal, and presentation skills.
• Self‑driven, collaborative, and able to thrive in a multidisciplinary research environment.

Preferred Qualifications

• Optical spiking neural networks and neuromorphic photonic architectures.
• Algorithm‑hardware co‑design for emerging computing technologies.
• Integrated photonic circuit and system design.
• Machine learning, deep learning, and AI system design.
• Neuromorphic computing and event‑driven processing techniques.
• PyTorch, TensorFlow, or similar machine learning frameworks.
• Experimental validation, simulation, and modeling of advanced hardware systems.
• Quantum dot lasers, resonant tunneling diodes, optical or electronic memristors, or related emerging technologies.
• Development of impactful use cases and technology demonstrators.

Success Factors

• Build productive collaborations across disciplines.
• Communicate complex concepts to diverse technical audiences.
• Translate research breakthroughs into meaningful applications.
• Take init