Dear all, Apparently, the attachement got lost. Here is the full description. Regards,

The Department of Complex Systems Engineering at ISAE-SUPAERO is offering an internship position, for a duration of up to 6 months, starting july (or as early as possible).

The candidate work will fall within the “Learning4Opt” project and will be tutored by E. Rachelson (ISAE-SUPAERO professor) and L. Mossina (PhD student).

The team is currently working on recurrent combinatorial optimization problems — problems that require the resolution of similar instances over time. Often, this process is time-constrained, leading to a trade-off between optimality and computation time. The main question investigated is, can we learn from past solutions? Can we guide the resolution of future instances and get faster and better results?

Examples of applications are: • Unit commitment in energy production • Project planning • Assignment problems • Satellite planning problems • and standard other Operations Research benchmarks.

Student profile: The candidate must be enrolled in a university program (Master’s degree or equivalent) to be eligible for funding. The work will involve a fair amount of coding in either C++ or Python and numerical experiments. There are also many opportunities for research work, depending on the candidate's affinities.

Academic background: • Majoring in Computer Science or • Strongly quantitative discipline, with coding experience • Interest in exploring applications of Machine Learning to Operations Research

Skills: • Confidence in programming, (Python and C++ highly desirable), • Basic Probability and Statistics, • Basic knowledge of Linear and Integer Programming Good level in English required, French not necessary.

Bibliography: • A. M. Alvarez, Q. Louveaux, and L. Wehenkel. A machine learning-based approximation of strong branching. INFORMS Journal on Computing, 29(1):185–195, 2017. • M. Kruber, M.E. Lübbecke, and Axel Parmantier. Learning when to use a decomposition. Technical Report 2016–037, Operations Research, RWTH Aachen University, November 2016. • A. Lodi and G. Zarpellon. On learning and branching: a survey. 2017. • E. Rachelson, A. B. Abbes, and S. Diemer. Combining mixed integer programming and supervised learning for fast re-planning. Tools with Artificial Intelligence (ICTAI), 2010.

*Emmanuel Rachelson* Associate professor - ISAE Supaero Dept. of Complex Systems Engineering http://people.isae.fr/emmanuel-rachelson On 16/06/2017 11:10, Emmanuel Rachelson wrote:

Dear all, An internship position is available in the ML & OR team at ISAE-SUPAERO, in Toulouse, France. See description attached to this message. Candidates should write to emmanuel.rachelson@isae-supaero.fr and luca.mossina@isae-supaero.fr. Regards,