We are seeking a motivated and innovative Post-Doctoral Research Fellow to conduct cutting-edge research in AI safety. The candidate will focus on curating data, aligning AI models, identifying gaps between academic research and industry practices, and developing tools to govern AI behavior. The position also requires regular publication in top-tier AI conferences and journals. This role offers the opportunity to contribute to the development of responsible and safe AI systems while working at the forefront of AI research.
Key Responsibilities:
1) Data Curation and Management: Collect, clean, and organize datasets relevant to AI safety research. Ensure data quality and accessibility for model training and evaluation.
2) Model Alignment and Development: Align AI models with safety objectives, ethical guidelines, and societal norms. Design and evaluate methods to prevent unsafe or unintended AI behavior.
3) Gap Analysis: Identify gaps between current AI safety research and industry practices. Propose actionable solutions and frameworks to address these gaps.
4) User Interviews and Research: Conduct interviews and surveys with stakeholders (users, developers, policymakers) to understand real-world challenges in AI safety. Integrate findings into research and tool development.
5) Tool Development: Develop practical tools, frameworks, or methodologies to govern and evaluate AI behavior. Prototype solutions that enhance AI interpretability, robustness, and compliance with ethical guidelines.
6) Research and Publication: Conduct high-quality, novel research in AI safety. Publish findings regularly in top-tier AI conferences and journals (e.g., NeurIPS, ICML, ICLR, AAAI, ACL).
Qualifications:
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Demonstrated research experience in AI safety, ethical AI, alignment, or related areas.
- Strong programming skills in Python and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch).
- Proven experience with data curation, analysis, and cleaning.
- Track record of publications in top AI/ML conferences and journals.
- Excellent written and verbal communication skills.
- Strong analytical and problem-solving abilities.
- Experience in user research, including conducting interviews and surveys.
- Familiarity with fairness, robustness, and interpretability in AI.
- Knowledge of industry trends and challenges in deploying safe AI systems.
- Ability to collaborate across interdisciplinary teams and with external stakeholders.