Research Intern (Quantum Computing)

The Quantum R&D Division at Fujitsu Research of India Pvt. Ltd. (FRIPL) combines the strengths of Quantum Computing, Information Theory, Artificial Intelligence and Software Engineering to build next-generation computational systems. As part of a global network of Fujitsu Quantum Labs across Japan, India, the USA, and Europe, the India team contributes to the Quantum Computing Stack, spanning hardware, firmware, compiler, simulators, algorithms, and applications.

We are seeking multiple talented researchers to join Fujitsu’s Quantum Technology R&D Internship Program.  As a research intern, you will conduct original research aligned with Fujitsu’s strategic vision for quantum computing.

Internship opportunity:

 We are inviting applications for a research internship at the intersection of the theory of open quantum systems, thermalisation and quantum algorithms (Fault tolerant/Early fault tolerant). 

 The internship is intended for candidates at the Master's level or above. This includes, current Masters students, PhD students and recent graduates with a strong interest in open quantum systems or quantum algorithms or both.

 Essential requirement:

1. Strong background in open quantum systems and statistical physics


2. Strong mathematical maturity in linear algebra and basic functional analysis


3. Ability to read and work through research papers independently


4. Good written communication skills and the ability to prepare clear technical notes and short presentations


5. Interest in rigorous theoretical work at the interface of open quantum systems, statistical physics and quantum algorithms

Preferred requirements:

1. Exposure to quantum algorithms (Hamiltonian simulation, Block encoding, Quantum singular value transformation etc.)


2. Programming experience in Python

Duration and mode:

1. Duration: 3 months (extendable to 3 more months based on performance and mutual interest)


2. Mode: Physical


3. Location: Bangalore, India

Application materials:

1. Updated CV


2. Links of relevant projects, thesis work, papers or pre-prints (if applicable)