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Thales is a global technology leader trusted by governments, institutions, and enterprises to tackle their most demanding challenges. From quantum applications and artificial intelligence to cybersecurity and 6G innovation, our solutions empower critical decisions rooted in human intelligence. Operating at the forefront of aerospace and space, cybersecurity and digital identity, we’re driven by a mission to build a future we can all trust.
In Singapore, Thales has been a trusted partner since 1973, originally focused on aerospace activities in the Asia-Pacific region. With 2,000 employees across three local sites, we deliver cutting-edge solutions across aerospace (including air traffic management), defence and security, and digital identity and cybersecurity sectors. Together, we’re shaping the future by enabling customers to make pivotal decisions that safeguard communities and power progress.
TOPIC : Speech Denoising
Description
This internship offers the opportunity to contribute to R&D on advanced AI Speech Denoising initiative aimed at improving speech clarity in real-world, noisy environments. The intern would combine deep learning, digital signal processing, and data-driven optimization to build robust models capable of separating human speech from complex background noise. The initial focus would be on specializing and fine-tuning state-of-the-art noise suppression AI models to achieve optimal denoising performance in selected acoustic environments.
Responsibilities:
- Data Collection & Preparation
- a) Collect, annotate, and preprocess speech and noise datasets from various environments.
- b) Implement scripts for mixing speech and environmental noise at different signal-to-noise ratios (SNRs) and perform quality control on generated data.
- Machine Learning Development
- a) Assist in training and fine-tuning deep learning models for speech denoising.
- b) Evaluate models using objective metrics (e.g., PESQ, STOI) and subjective listening tests.
- c) Experiment with architecture variations, training configurations, and hyperparameter tuning.
- System Integration & Evaluation
- a) Conduct performance benchmarking and error analysis.
- b) Document results, visualize findings, and present outcomes to the research team.
- Education: Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical discipline.
- Programming: Proficient in Python, with experience in NumPy, pandas, and preferably PyTorch.
- Machine Learning Knowledge: Familiar with deep learning fundamentals and general model training workflows.
- Hands-on experience building and evaluating state-of-the-art speech denoising systems.
- Exposure to end-to-end AI development, from data acquisition to deployment.
- Mentorship from researchers and engineers experienced in audio AI, deep learning, and signal processing.
- A practical understanding of how AI models integrate into real-world audio pipelines.
- Able to commit on a full-time basis for ideally 6 months (or a minimum of 5 months) from Jan 2026.
Key Skills
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