Due to NSA requirements, all qualified candidates must be US Citizen or a Green Card holder

This is a disruptive, hands-on research role focused on tackling fundamental scientific and conceptual problems in fiber-optic communication and advanced fiber sensing.

You will be responsible for inventing and implementing photonic subsystems with particular focus on developing components and signal processing techniques for optical communication and fiber sensing applications. The work will involve both proof-of-principle studies in a lab environment and field trials of developed prototypes, showcasing performance in real-world scenarios. You are expected to collaborate extensively, both within Nokia Bell Labs and with external partners.

To excel in this role, you should possess a potent blend of research excellence, experimental experience, technical depth, and programming proficiency.

Technical Foundation:

Education: Ph.D. degree or equivalent in a relevant field (e.g., electrical engineering, physics, computer science) with a specialization in optical metrology, fiber sensing, or fiber optics communication.

Experience: Preferred 3+ years of professional or postdoctoral technical experience in the field of optical metrology, fiber optic communication, fiber sensing, or machine learning.

Core Skills:

Excellent experimental and numerical simulation skills, with a proven track record in optical transmission and sensing technologies.

Prefered technical skills:

• Optical micropackaging:

Experience with the design and packaging of optical components. Experience with on-chip lasers and locking or stabilization circuits is highly desirable.

• Machine Learning: Strong practical experience with state-of-the-art machine learning tools and techniques, including deep learning frameworks. Experience with ML for optical communications or distributed fiber sensing is highly desired.

• Real-time DSP: Strong background in coherent signal processing techniques and implementations. Experience with FPGA design and real-time GPU implementations supporting optical digital signal processing algorithms is highly desired.

• Programming Mastery:

Exceptional programming skills, with a strong preference for proficiency in Python (including data science and ML libraries). Experience with C, CUDA, VHDL/Verilog is highly desired.

Research Innovation: Demonstrated significant research innovation and results, evidenced by high-impact publications in leading journals and/or recognized industry contributions.

Communication & Collaboration

Fluency: Professional fluency in English, both oral and written.

Presentation Skills:

Exceptional presentation skills, capable of clearly communicating complex technical concepts to diverse audiences (internal stakeholders, scientific peers, and conferences).

Interpersonal Skills:

Excellent interpersonal skills, fostering strong collaboration within a world-class research team.

As a research scientist, you will be expected to make fundamental contributions in one or multiple of the following areas:

• Portable ultra-stable lasers:

Design, conduct, and lead research projects investigating the optimization of ultra-narrow bandwidth laser systems and derived optical comb systems, including the fabrication, design, and packaging of related devices using state-of-the-art technologies. Demonstrate applications of ultra-stable lasers and combs for fiber sensing, time synchronization, and the stabilization of quantum communication links.

• Advanced Real-Time DSP Development:

Propose and investigate experimentally optimized coherent modulation formats for reflective fiber sensing interrogators. Contribute to real-time implementation of coherent transmission, fiber link stabilization, and fiber sensing systems using both FPGAs and GPUs. The major emphasis is on developing DSP schemes that minimize any penalty on coexisting coherent optical transceivers and facilitate integrating fiber sensing and optical metrology techniques into live networks.

• Real-time Event Identification and Analysis:

Develop and implement novel machine learning (ML) algorithms specifically tailored for long-distance reflective fiber-sensing systems. A particular emphasis is on real-time ML implementations, combing edge and cloud compute to combine streams from several field systems. Model development includes both developing foundational models and domain-specific model adaptation.

You are expected to publish results in top-tier optical conferences and journals.