Internships

2025 Opportunities

The Physics & Informatics (PHI) Lab is eager to welcome our next class of interns. NTT Research was launched in 2019 for the sole purpose of fostering fundamental research. Our internship program allows every participant to actively contribute to that research while learning from leading minds.

Internships duration varies from 3 months to 6 months depending on the project nature and intern preference. Applicants should be physicists, computer scientists, brain scientists and electrical engineers enrolled in PhD programs and have an interest in exploring the interdisciplinary space between quantum information science and neuroscience using optical technologies.

Internship forms should be submitted by Friday, March 28, 2025 to assure full consideration. In addition to financial compensation, summer housing assistance and travel allowances are available to qualified candidates.

Form for PHI Lab Internships

Publications Co-authored by Past Interns

"What shapes the loss landscape of self-supervised learning?"
Liu Ziyin*, Ekdeep Singh Lubana*, Masahito Ueda, and Hidenori Tanaka†
ICLR 2023 (The International Conference on Learning Representations)
NeurIPS 2022 Workshop: Self-Supervised Learning - Theory and Practice
"Mechanistic Mode Connectivity"
Ekdeep Singh Lubana, Eric J. Bigelow, Robert Dick, David Krueger, and Hidenori Tanaka
NeurIPS 2022 Workshop: Distribution Shifts (DistShift) Connecting Methods and Applications
"Geometric Considerations for Normalization Layers in Equivariant Neural Networks"
Max Aalto, Ekdeep Singh Lubana, and Hidenori Tanaka
NeurIPS 2022 Workshop: AI for Accelerated Materials Design
"CoRNN: Convex recurrent neural networks for interpreting brain dynamics"
Fatih Dinc, Adam Shai, Mark Schnitzer, Hidenori Tanaka
NeurIPS (Advances in Neural Information Processing Systems)2023​
"Noether’s Learning Dynamics: Role of Symmetry Breaking in Neural Networks"
Hidenori Tanaka, Daniel Kunin
NeurIPS (Advances in Neural Information Processing Systems) 2021
"Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning"
Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka
NeurIPS (Advances in Neural Information Processing Systems), 2021
"Image sensing with multilayer, nonlinear optical neural networks" Tianyu Wang, Mandar M. Sohoni, Logan G. Wright, Martin M. Stein, Shi-Yuan Ma, Tatsuhiro Onodera, Maxwell G. Anderson, Peter L. McMahon
Nature x, 2023
"A Self-Similar Sine-Cosine Fractal Architecture for Multiport Interferometers"
Jasvith Raj Basani, Sri Krishna Vadlamani, Saumil Bandyopadhyay, Dirk R. Englund, Ryan Hamerly
Nanophotonics, 2023
"Coherent SAT Solver"
Sam Reifenstein, Timothee Leleu, Tim McKenna, Marc Jankowski, Myoung-Gyun Suh, Edwin Ng, Farad Kyoyratee, Yoshitaka Inui, Zoltan Toroczkai, and Yoshihisa Yamamoto
Adv. Opt. Photon, 2023
"Benchmark study on quantum algorithms for combinatorial optimization problems"
Krishanu Sankar, Artur Scherer, Satoshi Kako, Sam Reifenstein, Navid Ghadermarzy, Willem B. Krayenhoff, Yoshitaka Inui, Edwin Ng, Tatsuhiro Onodera, Pooya Ronagh and Yoshihisa Yamamoto
npj Quantum Information, 2024
"Hyperspectral In-Memory Computing with Optical Frequency Combs and Programmable Optical Memories"
Mostafa Honari, Byoung Jun Park, Yoshihisa Yamamoto, and Myoung-Gyun Suh
Optica, 2024
"Combinatorial clustering with a coherent XY machine"
Kyungduk Kim, Masahito Kumagai, and Yoshihisa Yamamoto
Optica, 2024
"Image sensing with multilayer, nonlinear optical neural networks"
Tianyu Wang, Mandar M. Sohoni, Logan G. Wright, Martin M. Stein, Shi-Yuan Ma,
Tatsuhiro Onodera, Maxwell G. Anderson, Peter L. McMahon
"Positive-P Gaussian model of measurement feedback coherent Ising machines with amplitude control and Zeeman terms"
Yoshitaka Inui, Mastiyage Don Sudeera Hasaranga Gunathilaka, Satoshi Kako, Toru Aonishi, and Yoshihisa Yamamoto
Communications Physics, 2022

Examples of potential projects for 2025 Internship:

Feasibility study for an experimental coherent Ising machine based on measurement feedback in a novel few-photon limit
Physical neural networks with lithium niobite nanophotonics
Delocalized photonic training of DNNs using coherent Netcast
Dissecting the mechanistic basis of concept learning
Temporal Trapping for Ultrafast Optical Strong Coupling
Squeezed vacuum for quantum communication and control
Physical neural networks with CMOS electronics
TFLN vertical-cavity surface-emitting OPOs
Novel measurement schemes for 2D materials
Inverse design of nonlinear waveguides
Physics of driven-dissipative non-linear networks in the presence of single-photon on-site non-linearity
Driving nonlinear topological photonics by structured non-Hermitian lattices
Benchmarking against other quantum machines and modern heuristics
Dynamics of topological and non-Hermitian photonic systems
Single photon quantum non-linearity from gate-defined dots
High-Speed Time-Multiplexed Optical Computing Systems
In-situ periodic poling of ferroelectric thin films
Advanced approaches to chip-to-fiber coupler
Hardware error correction in photonics
Monolithic sync pumped TFLN OPOs
Electronic-photonic integration for machine learning
Frequency-multiplexed combinatorial optimization solver utilizing optical frequency combs


Internship Benefits

One-on-One Mentoring
Optical Laboratory
at Sunnyvale, CA
Journal Club on Quantum Information and Neural Networks

A total of 26 graduate and undergraduate students from the United States, France, Italy and Japan participated in the PHI Lab internship program. Their project titles included:

Geometric Considerations for Normalization Layers in Equivariant Neural Networks
Learning representation of the brain activity via convex recurrent neural networks
Energy Landscape and Landau Theory of Self-Supervised Learning
A Mechanistic Lens on Mode-Connectivity in Neural Network Loss Landscapes
Image sensing with Optical Neural Networks
Towards scalable physical neural networks with thin-film lithium niobate
A Photonic Ising Machine using Ultra-Low Optical Energy
Hybrid Ising machines combining dissipative and conservative dynamics
Optimal Curriculum Learning Strategies for Sequential and Trail-Tracking Tasks
SCoherent SAT Solvers
Photonic Landau levels in an exciton-polariton microcavity
Scaling analysis of Grover’s algorithm for 3-SAT problems
Squeezed-Quantum-Noise-Assisted Optimization for Quadratic Binary Problems by CIM-CAC
Effects of quantum noise on the performance of optimization on OPO networks
Creating lateral quantum wells in monolayer semiconductors by an electrostatic confinement mechanism
Frequency-Multiplexed C-band Free-Space Optical Platform for Matrix-Vector Multiplication
Simulation of a Quantum Time-multiplexed Photonic Resonator Network
Algorithm and Error Analyses of the Simulation of Time-Dependent Hamiltonians
Measuring Geometry of Waveguide Using AFM
A Self-Similar Sine-Cosine Fractal Architecture for Multiport Interferometers
Hard mask development for next-generation lithium niobate processing
Efficient Hamiltonian Encodings for Simulation of Electronic Structure Hamiltonian
Modular Quantum Algorithms as Functional Transforms
Measurements' technique on 2D semiconductors
IR cavity characterization and outlook

About PHI Lab

The Physics & Informatics (PHI) Lab uncovers fundamental principles and novel technologies that advance our information processing beyond the state of the art. We explore the interdisciplinary space between quantum information science and neuroscience using optical technologies. We foster an environment for physicists, computer scientists, brain scientists and electrical engineers to work together to build a new era of computation framework.

While we are relatively new to the United States, NTT (Nippon Telegraph and Telephone) has over 70 years of history in Japan supporting basic research and delivering breakthroughs to the real world.