PhD Research Assistant / PhD Candidate — Audio Machine Learning & Signal Processing

Job summary

Research voice deepfake detection and anti-spoofing, prepare speech datasets, and run training and evaluation experiments on real-world and telephone-quality audio. Investigate generalization and error patterns, document reproducible experiments, and help turn research findings into product improvements and academic submissions.

Job details

FinOptima Solutions is developing real-time voice deepfake detection and AI interaction intelligence for banks and financial institutions. We have an existing model, research paper, datasets, GPU access and cloud infrastructure. We are now improving the model’s performance across different speakers, recording environments and telephone-quality audio. **The role We are looking for a hands-on Research Assistant who is currently pursuing a PhD in machine learning, speech processing, audio AI, signal processing, electrical engineering or a closely related field. You will work with our CTO, machine learning team and academic advisor to improve the existing model and prepare it for controlled pilots. This is a practical research role involving code, datasets, experiments and model evaluation—not purely theoretical work. What you will do Research voice deepfake detection, audio provenance and anti-spoofing methods Identify and prepare genuine and synthetic speech datasets Process real-world and telephone-quality audio Run training, fine-tuning and model-evaluation experiments Investigate cross-domain and cross-speaker generalization issues Analyze false positives and false negatives Test preprocessing, calibration and audio-window aggregation methods Maintain reproducible experiment logs and technical documentation Support future academic papers and research submissions Help translate research findings into practical product improvements Requirements Currently pursuing a PhD in a relevant technical discipline or already has a PhD Hands-on experience with audio or speech machine learning Strong Python skills and experience with PyTorch or TensorFlow Understanding of signal processing, audio preprocessing and model evaluation Ability to read academic papers and implement research methods Organized, proactive and comfortable working independently Preferred experience Voice deepfake detection, anti-spoofing or speaker verification ASVspoof, Common Voice or similar audio datasets Access to university laboratory or GPU resources Academic writing and publication experience Interest in cybersecurity, responsible AI and financial services This is an equity-only opportunity for a PhD candidate who wants to contribute to applied research with real commercial and societal impact. Publication authorship will be based on substantive research contributions.

What you’ll do

Research voice deepfake detection and anti-spoofing, prepare speech datasets, and run training and evaluation experiments on real-world and telephone-quality audio. Investigate generalization and error patterns, document reproducible experiments, and help turn research findings into product improvements and academic submissions.

Requirements

The candidate must be pursuing or have completed a PhD in a relevant technical discipline and have hands-on audio or speech machine learning experience. Strong Python skills, experience with PyTorch or TensorFlow, knowledge of signal processing and model evaluation, and the ability to implement research methods are required.

Listed skills

• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Audio Machine Learning
• Speech Processing
• Python
• PyTorch
• TensorFlow
• Signal Processing
• Audio Preprocessing
• Model Evaluation
• Voice Deepfake Detection
• Anti-Spoofing
• Speaker Verification
• Dataset Preparation
• Model Training
• Cross-Domain Generalization
• Experiment Documentation

Job areas

• Science & Research
• Technology
• Software
• Data & Analytics
• Finance & Accounting

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