The Tepper School of Business at Carnegie Mellon University is looking to solve scientific problems from fresh angles using creative interdisciplinary approaches, and is seeking a Postdoctoral Research Associate to join their team to research in the intersection of discrete optimization and machine learning, including algorithmic fairness.
Requirements
- PhD in a related field required
- Experience working on and publishing refereed papers on problems related to discrete and continuous optimization and machine learning
- Strong analytical and problem-solving skills
- Organization and planning skills
- Strong oral and written communication skills
Responsibilities
- Research in the intersection of discrete optimization and machine learning, including algorithmic fairness
- Formulation of new problems and research directions and translating topical issues into algorithmic problems
- Designing new algorithms and investigating their performance on synthetic and actual data
- Participate in writing up the results and submission for scientific publication
- Collaborate with and mentor doctoral students engaged in the projects
- Other duties as assigned
Other
- Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University
- Ability to effectively interact with a varied population of internal and external partners at a high level of integrity
- Must be currently legally authorized to work for CMU in the United States
- PhD in a related field required
- Ability to work full-time
