Ph.D. position in ML and Combinatorial Optimization

[Ferdinando Fioretto]

Dear colleagues,

I would be grateful for helping me in disseminating the availability of a PhD position at Syracuse University on the topics of Machine Learning and Combinatorial Optimization. 

Thank you and best regards,

Ferdinando Fioretto

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A PhD position is available for candidates interested in the intersection of deep learning and combinatorial optimization. 

Where: Syracuse University, NY, Department of Computer Science

When Flexible, but preferred starting is January 2022 

Lab group lead: Ferdinando Fioretto (www.nandofioretto.com)

Topics of interest

Topics of interest include, but are not limited to: 

• Supervised Learning for speeding up the resolution of constrained optimization problems; 
• Reinforcement Learning for dynamic and combinatorial problems; 
• Graph Neural Network models for graph-structured constrained optimization problems; 
• Theoretical guarantees for ML-enhanced constraint optimizers; 
• Physics informed deep learning; 

The project will combine fundamental aspects of optimization, constrained reasoning, and learning to develop integrated optimization and learning systems.

Candidate Requirements
The ideal candidate must have the ability to work in a stimulating and fast-paced environment and will have a strong background in mathematics and optimization theory as well as a strong interest in machine learning and constraint reasoning. 

Students who majored in Computer Science, Mathematics, Statistics, or Physics are welcome to apply. 

An MS degree and/or publications in leading international venues will be an advantage. 

To Apply

Applications should be submitted at ffio...@syr.edu and candidates should include their statement of purpose, resume, and transcript (if available).

Informal inquiries are also welcome and may be sent to ffio...@syr.edu. 

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Ferdinando Fioretto, Ph.D.

Assistant Professor

EECS Dept. Syracuse University

web: nandofioretto.com