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- Tasks: Design and implement AI-based video decoders to enhance video compression efficiency.
- Company: Join InterDigital, a leader in wireless and video technology innovation.
- Benefits: Gain hands-on experience, mentorship from experts, and contribute to groundbreaking research.
- Other info: Opportunity to generate patents and publications during the internship.
- Why this job: Make an impact in AI and video tech while developing skills for your future career.
- Qualifications: MSc in relevant fields with skills in deep learning, computer vision, and Python.
The predicted salary is between 20000 - 30000 ÂŁ per year.
About InterDigital
InterDigital is a global research and development company focused primarily on wireless, video, artificial intelligence (“AI”), and related technologies. We design and develop foundational technologies that enable connected, immersive experiences in a broad range of communications and entertainment products and services. We license our innovations worldwide to companies providing such products and services, including makers of wireless communications devices, consumer electronics, IoT devices, cars and other motor vehicles, and providers of cloud-based services such as video streaming. As a leader in wireless technology, our engineers have designed and developed a wide range of innovations that are used in wireless products and networks, from the earliest digital cellular systems to 5G and today’s most advanced Wi-Fi technologies. We are also a leader in video processing and video encoding/decoding technology, with a significant AI research effort that intersects with both wireless and video technologies. Founded in 1972, InterDigital is listed on Nasdaq.
Summary
In this internship at the London AI Video Lab, the objective is to design computationally efficient video decoders in an AI-based video compression codec. Current AI-based video compression models outperform conventional codecs, like HEVC, VVC and AV1. However, this comes at the cost of impractical compute requirements: at decode, current AI-based video compression decoders are several orders of magnitude more complex than conventional video compression decoders. The goal of the internship is to design efficient AI-based decoders that leverage spatial sparsity to reduce their computational complexity. This work will be seen as one step forward toward the deployment of end-to-end trained AI-based video compression models. The goal will be to find and review potential existing methods of spatial sparsity in AI-based video models. In a second step, spatially sparse AI-based decoders will be designed, implemented and integrated into the London AI Video Lab’s end-to-end trained video compression model. The performance of the proposed solution will be evaluated and compared to existing models. The internship will take place in the London AI Video Lab. The intern will be mentored by scientists and will be part of a research project developing end-to-end trained AI-based video compression models.
Duration: 5-6 months, starting January-April 2026
Responsibilities
- State-of-the-art and analysis of existing solutions
- Implementation of a computationally efficient AI-based video decoder
- Evaluation and reporting of results
Qualifications
- MSc in Computer Science, Machine Learning, Mathematics, Physics or a related field
- Deep learning, computer vision, Python, PyTorch
Expected Outcomes: Apart from the expected outcome that corresponds to the spatially sparse video model and its evaluation, this internship will be expected to generate patents and publications.
Location: London, UK
Intern, Spatially Sparse AI-based video decoders employer: INTERDIGITAL, Inc.
Contact Detail:
INTERDIGITAL, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Intern, Spatially Sparse AI-based video decoders
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at InterDigital. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Prepare for interviews by diving deep into AI and video compression topics. Show us you’re not just a candidate, but someone who’s genuinely excited about the field!
✨Tip Number 3
Don’t forget to showcase your projects! Whether it’s a GitHub repo or a personal website, let us see what you’ve been working on. It’s a great way to stand out!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Intern, Spatially Sparse AI-based video decoders
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the internship role. Highlight your skills in deep learning, computer vision, and any relevant projects you've worked on. We want to see how your background aligns with our focus on AI-based video decoders!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and video compression, and explain why you're excited about this internship at InterDigital. Let us know what makes you a great fit for our team.
Showcase Relevant Projects: If you've worked on any projects related to video processing or machine learning, make sure to mention them! We love seeing practical applications of your skills, so don’t hold back on sharing your achievements.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you're serious about joining our team!
How to prepare for a job interview at INTERDIGITAL, Inc.
✨Know Your Stuff
Make sure you brush up on the latest advancements in AI-based video compression and spatial sparsity. Familiarise yourself with key terms and concepts mentioned in the job description, like HEVC, VVC, and AV1. This will show your interviewers that you're genuinely interested and knowledgeable about the field.
✨Showcase Your Skills
Prepare to discuss your experience with Python and PyTorch, as well as any relevant projects you've worked on. Bring examples of your work, especially if they relate to deep learning or computer vision. This will help demonstrate your practical skills and how they align with the internship's responsibilities.
✨Ask Smart Questions
Come prepared with insightful questions about the role and the team. Inquire about the specific challenges they face in developing AI-based decoders or how they measure success in their projects. This not only shows your enthusiasm but also helps you gauge if the internship is the right fit for you.
✨Be Ready to Collaborate
Since you'll be working closely with scientists and other team members, highlight your teamwork skills. Share examples of how you've successfully collaborated on projects in the past. Emphasising your ability to work well in a team will reassure them that you're a good fit for their collaborative environment.