Research Intern

Research Intern

Job Location:

Santa Clara, California

Location Flexibility:
Multiple Locations in Country

Req

Posting

Start Date:

1/16/26

At Fujitsu, we are driven by our purpose to make the world more sustainable by building trust in society through innovation.

We have been a pioneer in technology and innovation for over 80 years, and we are committed to using our expertise to help businesses and organizations transform for the digital age. We believe that digital transformation is essential to creating a more sustainable future. That's why we are working with our customers to develop solutions that can help them reduce their environmental impact, improve their efficiency, and create a more equitable society.

We are committed to contributing to the United Nations Sustainable Development Goals (SDGs). These goals are a blueprint for a better future for all, and we believe that technology can play a vital role in achieving them.

If you share our passion for making a meaningful impact on the world, we invite you to join our global family of 130,000 employees spanning more than 50 countries. We are a diverse workforce, and we offer a wide range of opportunities for you to grow and develop your career.

Together, we can create a more sustainable future for all.

Research Intern at Fujitsu's Converging Technology Laboratory (AI for Urban systems) 

At Fujitsu's Converging Technology Laboratory (CT Lab), we focus on integrating research across diverse technical domains to create solutions that reflect the values of an increasingly complex and diverse society. We believe addressing these challenges requires a new paradigm that combines multidisciplinary knowledge spanning computer science, natural sciences, and the humanities. Our mission is to develop scientific solutions that help guide society toward a more sustainable and prosperous future.

Our internships offer an excellent opportunity to expand your career with hands-on experience and the chance to tackle real-world challenges through deep learning applications addressing urban and social issues ranging from mobility and sustainability to healthcare and beyond. We are seeking individuals who learn quickly, navigate complexity, and bring creativity, passion, and strong communication skills to solving challenges others haven't

Job responsibilities 

+ Design and develop deep learning methods to solve complex challenges across physical, social, and environmental science domains.

+ Collaborate with our team members and external researchers

+ Publish research in journals and conferences. Transfer the deliverables to patents, conference presentations, and workshops.

Key focus areas

Fine-tuning LLMs and foundation models or other deep learning methods on geospatial, transportation, socio-demographic, and healthcare datasets to analyze social structures and simulate urban dynamics. This involves leveraging machine learning for predictive modeling and scenario simulation to understand patterns of (1) mobility or (2) social interactions within complex urban systems.

Requirements 

+ Currently enrolled in a university pursuing a PhD degree in Computer Science, Physical Sciences, Health sciences, and other relevant fields for the entire duration of the internship.

+ Solid programming skills with experience training and evaluation ML pipelines:
Python, Deep Learning Frameworks (e.g. PyTorch).

+ Strong track record of demonstrating through accomplishments such as research publications, impactful projects, or success in technical competitions.

+ Excellent communication and collaboration skills through written communication and verbal interaction.

Who we are looking for

+ Hands-on experience with GPU-accelerated deep learning frameworks like Py Torch

+ Familiarity with fine-tuning large models using platforms such as Hugging Face

+ Experience working with diverse multimodal datasets or simulations from physical and social sciences or related domains.

+ Previous experience working with cluster schedulers (e.g., Slurm)

+

Experience with large-scale simulations and ML model training is plus but not required.

The internship duration is 3 months and part time (20hours / week). Locations are…