IN-CYPHER is hiring an AI Research Intern to work across Themes 3 and 4. You will explore new approaches to synthetic data generation under differential privacy aiming to push the utilityprivacy frontier for text and multimodal data. A key part of the role is building and validating privacy auditing tools such as membership inference attacks tailored to synthetic datasets and designing evaluation protocols to quantify privacy risk.
Requirements:
Education: Currently enrolled in or have completed an undergraduate or graduate program in Computer Science/Engineering or a closely related ML/AI field.
Background: Experience in software development including:
Proficient coding skills (e.g. Python)
Deep learning frameworks (e.g. PyTorch)
Experience with LLMs/NLP and/or AI security (e.g. privacy robustness)
Main Duties:
- Independently reproduce open-source SOTA methods (e.g. set up virtual environments replicate training/evaluation pipelines) understand codebases and read related papers.
- Develop and improve method frameworks under guidance; select and test new datasets; and produce clear reproducible experiment reports.
- Plan and execute work efficiently with good time management communicate progress promptly and collaborate effectively with the team.
- Uphold high standards of research integrity.
Duration: 6 months
Stipend: $1500 per month
Informal enquiries are greatly welcome and can be directed to Dr Viktor Schlegel
Questions about the recruitment process should go to the HR at Imperial Global Singapore
Required Experience:
Intern
IN-CYPHER is hiring an AI Research Intern to work across Themes 3 and 4. You will explore new approaches to synthetic data generation under differential privacy aiming to push the utilityprivacy frontier for text and multimodal data. A key part of the role is building and validating privacy auditing...
IN-CYPHER is hiring an AI Research Intern to work across Themes 3 and 4. You will explore new approaches to synthetic data generation under differential privacy aiming to push the utilityprivacy frontier for text and multimodal data. A key part of the role is building and validating privacy auditing tools such as membership inference attacks tailored to synthetic datasets and designing evaluation protocols to quantify privacy risk.
Requirements:
Education: Currently enrolled in or have completed an undergraduate or graduate program in Computer Science/Engineering or a closely related ML/AI field.
Background: Experience in software development including:
Proficient coding skills (e.g. Python)
Deep learning frameworks (e.g. PyTorch)
Experience with LLMs/NLP and/or AI security (e.g. privacy robustness)
Main Duties:
- Independently reproduce open-source SOTA methods (e.g. set up virtual environments replicate training/evaluation pipelines) understand codebases and read related papers.
- Develop and improve method frameworks under guidance; select and test new datasets; and produce clear reproducible experiment reports.
- Plan and execute work efficiently with good time management communicate progress promptly and collaborate effectively with the team.
- Uphold high standards of research integrity.
Duration: 6 months
Stipend: $1500 per month
Informal enquiries are greatly welcome and can be directed to Dr Viktor Schlegel
Questions about the recruitment process should go to the HR at Imperial Global Singapore
Required Experience:
Intern
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