HPE Labs - Postdoctoral Research Scientist: Generative AI For Photonic And Analog Electronic Design Automation

HPE Labs - Postdoctoral Research Scientist: Generative AI for Photonic and Analog Electronic Design Automation

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

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.

About HPE Labs

The Large-Scale Integrated Photonics Lab (LSIP) at HPE Labs is currently seeking a highly qualified post-doc to accelerate research towards new applications, core methodologies and technologies. HPE Labs is the central, international research organization of Hewlett Packard Enterprise (HPE), dedicated to creating breakthrough technologies that shape future markets and deliver competitive advantages for HPE. Within HPE Labs, the LSIP Lab pioneers next-generation optical, analog electronic, and quantum computing systems, bridging fundamental science with real-world adoption.

Role Overview

We are seeking a postdoctoral researcher to define and execute an ambitious research agenda at the intersection of generative AI and algorithm-hardware co-design for next-generation photonic and analog electronic design automation (EDA).

You will explore, develop, and validate AI-assisted methodologies that accelerate the design, optimization, and verification of optical and analog electronic accelerators. You'll collaborate closely with a multidisciplinary team of machine learning experts, software developers, computer scientists, fabrication specialists, and experimentalists to drive high-impact results that can translate into products, publications, and patents.

We expect all our researchers (including interns and post-docs) to provide thought leadership and technical influence both internally and externally to HPE, as well as take innovative ideas and make them real – contributing along the full range from initial novel ideas to design, development, implementation, evaluation, and technology transfer. The ideal candidate can thrive in an applied research environment, balancing significant technical and scientific contributions with the ability to bring such contributions to practice through innovative solutions that address the needs of our customers and partners. We expect the successful candidate to collaborate with HPE Labs research teams as well as with external partners, and to work in alignment with HPE's broader innovation community.

What You'll Do

• Conduct research on applying modern generative AI tools to photonic and analog EDA problems (inverse design, surrogate modeling, constraint-aware optimization, layout generation, verification).
• Advance algorithm-hardware co-design for analog accelerators (optical, in-memory, neuromorphic), leveraging performance- and physics-aware system models.
• Prototype tools, build reproducible pipelines, and benchmark against state-of-the-art methods.
• Publish and disseminate results at top venues, contribute to patents and internal technology transfers.
• Potentially collaborate with fabrication and experimental teams to validate models on real hardware and datasets.

Minimum Qualifications

• PhD in Electrical Engineering, Photonics, Computer Science, Applied Mathematics, Physics, or a closely related field.
• Demonstrated enthusiasm for generative AI research, especially its application to optical/analog electronic design automation.
• Strong publication track record in relevant areas.
• Proven ability to work both independently and collaboratively in multidisciplinary environments.
• Excellent English written and verbal communication skills.

Preferred Qualifications

• Python proficiency and deep experience with PyTorch, JAX, or TensorFlow.
• Broad knowledge of modern ML and optimization (gradient-based, evolutionary, Bayesian, reinforcement learning).
• Hands-on experience with generative architectures (diffusion, flow-based, and large language models), including training, conditioning, and evaluation.
• Strong analytical, numerical, and modeling skills (physics-informed ML, surrogate modeling, PDE/ODE solvers, Monte Carlo methods).
• Working knowledge of optical, analog in-memory, or neuromorphic computing.
• Prior experience in algorithm–hardware co-design (co-optimization of architectures, algorithms, and physical constraints)

Accountability, Action Planning, Active Learning, Active Listening, Bias, Business, Calendar Management, Coaching, Computer Literacy, Creativity, Critical Thinking, Design Thinking, Empathy, Follow-Through, Group Problem Solving, Growth Mindset, Intellectual Curiosity (Inactive), Long Term Planning, Managing Ambiguity, Office Administration, Policy and procedures, Recordkeeping, Risk Assessment, Software Development {+ 5 more}

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.