Research Intern - Digital Climate

Research Intern at Fujitsu's Converging Technology Laboratory (Santa Clara, CA) 

The Converging Technology Laboratory (CT Lab) at Fujitsu specializes in combining research in multiple technical fields to address values in the increasingly diverse society. We believe this situation requires a new approach to combine multidisciplinary knowledge including natural science, and humanities. We strive to provide an evidence-based scientific approach to shape public policies and economic activities.

We're in search of a highly motivated intern to join our CT Lab located in Silicon Valley. This dynamic internship opportunity will concentrate on leveraging deep learning techniques with Synthetic Aperture Radar (SAR) data for climate prediction. It presents a distinctive chance to contribute to pioneering research at the intersection of climate science and artificial intelligence, providing hands-on experience with cutting-edge technologies and methodologies.

Fujitsu is the largest IT company in Japan and among the largest in the world. Fujitsu’s mission is to make the world more sustainable by building trust in society through innovation. Join us in shaping the future of the world.  

The internship duration is at least 3 months and a maximum of 5 months. 

 Job Responsibilities 

1. Collaborate with our research team to explore the potential of deep learning techniques for analyzing SAR data in the context of climate prediction.
2. Develop and implement deep learning models and algorithms to extract meaningful insights from SAR imagery and other relevant datasets.
3. Conduct experiments and evaluate the performance of deep learning models for various climate prediction tasks, such as weather forecasting, precipitation estimation, and environmental monitoring.
4. Explore innovative approaches to improve the accuracy, efficiency, and robustness of deep learning-based climate prediction systems.
5. Work closely with domain experts to understand the requirements and challenges of climate prediction applications and tailor deep learning solutions accordingly.
6. Publish research papers in scientific journals and conferences. Showcase the work via presentations in talks, conferences, workshops, and competitions.

 Requirements 

1. Currently enrolled in a Master's or PhD program in a relevant research program.
2. Experience with SAR data processing techniques, and remote sensing concepts.
3. Solid understanding of deep learning fundamentals and experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
4. Proficiency in programming languages such as Python and experience with scientific computing libraries (e.g., NumPy, SciPy) is preferred.
5. Experience in evaluating tools and technologies in processing data from diverse but specialized fields of science.  

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