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Generative AI Research Internship
Generative AI Research Internship - Intel Corporation
Summary
Push the boundaries of artificial intelligence with the Generative AI Research Internship at Intel! This program offers a unique opportunity for highly motivated students to join a team of leading researchers exploring the cutting edge of generative AI. Contribute to groundbreaking projects that leverage this powerful technology to revolutionize various industries.
Qualifications
- Pursuing a Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related field.
- Strong foundation in machine learning principles, including deep learning and neural networks.
- Familiarity with generative AI models (e.g., GANs, VAEs) and their applications (beneficial).
- Experience with programming languages like Python and deep learning frameworks (PyTorch, TensorFlow) is essential.
- Excellent research skills, with the ability to independently conduct literature reviews and analyze data.
- Strong communication and collaboration skills to effectively present findings and work with a research team.
Responsibilities
- Participate in ongoing research projects focused on advancing generative AI technologies.
- Assist with tasks like data collection, model development, experimentation, and analysis of results.
- Contribute to brainstorming sessions and propose innovative research directions within generative AI.
- Stay up-to-date on the latest advancements in the field and present research findings to the team.
- Potentially document research progress and co-author technical papers for publication.
Benefits
- Gain invaluable experience working on cutting-edge generative AI research alongside industry leaders.
- Deepen your knowledge of machine learning and its applications in real-world scenarios.
- Develop advanced research skills and contribute to groundbreaking discoveries in AI.
- Build a strong network within the AI research community and gain valuable mentorship.
- Be at the forefront of technological innovation with the potential to shape the future of generative AI.
Location
Fully Remote
Deadline: May 4, 2024
