Internship: Quadratic Assignment Problems
The Data Analytics group at MERL is seeking a highly motivated intern to work on the development of novel optimization algorithms for quadratic assignment problems (QAPs). The target applications span a broad range of areas including markets, transportation and scheduling. Successful candidate will collaborate with MERL researchers to develop and implement new algorithms, conduct experiments, and prepare results for publication. Ideal candidate would be senior PhD students with experience in one or more of the following areas: mixed integer programming, constraint programming, semidefinite programming. Strong programming skills and fluency in C++/Matlab/Python are expected. Prior experience with popular optimization packages such as Ipopt, Gurobi, Cplex is a plus. The duration of the internship is expected to be 3 months. Start date is flexible.
Research Area: Data Analytics
Contact: Arvind Raghunathan