Assistant Professor
About The Position
This early career hire will focus on foundational statistical and optimization methods for safe and reliable AI, with applications in biomedicine and public health. Areas of interest include, but are not limited to, robust and stochastic optimization, generative and foundation models, reliable and robust machine learning, uncertainty quantification, sequential decision-making, and AI systems operating under uncertainty in high stakes environments. The secondary appointment in Biostatistics will facilitate close collaboration with applied researchers and provide pathways for translating methods into practice. Primary responsibilities of the position will include high-quality research, publishing in peer-reviewed journals and broader dissemination, seeking external funding for research, teaching undergraduate and graduate courses, contributing to research mentoring of doctoral students, and engaging in departmental, university, and professional service activities.
Requirements
- Focus on foundational statistical and optimization methods for safe and reliable AI
- Applications in biomedicine and public health
- Research and/or teaching interests that make substantive connections with related fields
- Excited to engage in cross-disciplinary conversations and collaborations
Nice To Haves
- Robust and stochastic optimization
- Generative and foundation models
- Reliable and robust machine learning
- Uncertainty quantification
- Sequential decision-making
- AI systems operating under uncertainty in high stakes environments
Responsibilities
- Conduct high-quality research
- Publish in peer-reviewed journals and broader dissemination
- Seek external funding for research
- Teach undergraduate and graduate courses
- Contribute to research mentoring of doctoral students
- Engage in departmental, university, and professional service activities
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
