Deadline:
As soon as possible
Location(s)
Korea, South
Seoul
Overview
Details
General Summary:
Qualcomm is a leading On-Device AI company, unlocking new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform On-Device AI's potential into world-changing technologies and products. This is the Invention Age - and this is where you come in.
We are seeking a passionate and driven research interns to join our team in advancing state-of-the-art speech-language technologies. This internship offers a unique opportunity to contribute to foundational and applied research in speech-based large language models (LLMs), multimodal emotion understanding, and on-device conversational AI agents. The ideal candidate will have a strong background in speech recognition, text-to-speech, emotion recognition, spoken dialogue systems, or multi-modal generative models, with a focus on building intelligent systems that understand and respond empathetically to human communication. Selected candidates will work on one or more of the following areas:
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Full-duplex and empathetic spoken dialogue system
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Representation learning of audio and speech data
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Multimodal emotion recognition using speech and text
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Speech-language model adaptation and fine-tuning for on-device deployment
Opportunity is About
Eligibility
Candidates should be from:
Description of Ideal Candidate
Minimum Qualifications:
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Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical and Electronic Engineering, or a related field
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Proficiency in Python and experience with machine learning frameworks (e.g., PyTorch)
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Solid understanding of speech processing or natural language processing concepts
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Availability for a minimum of 6 months
Preferred Qualifications:
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Prior research or hands-on project experience in one or more of the following areas: speech recognition, text-to-speech, speech self-supervised learning, speech emotion recognition, or large language models
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Strong background in representation learning for speech and audio data
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Experience with multimodal generative AI, integrating speech, text, and/or visual modalities
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Proven track record of academic contributions, including research publications or presentations at top-tier conferences
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Broad and in-depth understanding of machine learning and deep learning principles, algorithms, and architectures
Dates
Deadline: As soon as possible
Cost/funding for participants
Un-save Opportunity
Internships, scholarships, student conferences and competitions.
