Open Postdoctoral Position

The School of Engineering and Sciences at Tecnológico de Monterrey invites applications for a Postdoctoral Fellow within the Research Group in Advanced Artificial Intelligence. The successful candidate will be engaged in developing methods and algorithms in the bio-inspired computing track, related to various projects in hyper-heuristics and multi-objective optimization, and will be working in close collaboration with Dr. Hugo Terashima-Marin, and with Dr. Carlos A. Coello-Coello, Professor at CINVESTAV and recently appointed Faculty of Excellence at Tecnológico de Monterrey.

Research Issues:

Hyper-heuristic and multi-objective algorithms have gained attention in recent years and a combination of both techniques seem to have a great potential for solving complex optimization problems.  In this respect, there are still many problems that need to be addressed. We want to investigate some of those challenges with the intention to respond to some interesting research questions. The following are some issues we want to look into:

- Multi-objective hyper-heuristics.- We are interested in exploring the potential use of hyper-heuristics for solving multi-objective optimization problems more efficiently and effectively, starting with basic algorithms on both techniques.

- Automatic generation of heuristics and hyper-heuristics in the context of multi-objective optimization.- Although we have some initial researchinvestigation on this issue, there is still work to do for combinatorial and continuous problems.

- Generation of Hybrid hyper-heuristic models and multi-objective algorithms (metaheuristics-local search), constructive-perturbation, selection-generation, offline-online, lifelong learning, etc.).

- Extending hyper-heuristic development for impacting on multi-objective practical and real-world problems (in the context of smart cities).

- Development of cross-multiple-domain hyper-heuristics in the context of multi-objective optimization.- The idea on this topic is to produce more general and reusable methods, that is, hyper-heuristics that could be applied (with none or few modifications) to solve a wide range of multi-objective instances from different domains.

- Time analysis of multi-objective hyper-heuristics and comparative studies, considering the impact of the hyper-heuristic representation and generation model in the quality of solutions. These considerations are yet to be explored in the current literature.

Qualifications:

• PhD in Computer Science, Artificial Intelligence o related areas (preferably degree granted in 2017 or upwards).
• Strong scientific production (JCR Journals  and/or international conferences)
• Strong programming background.
• Excellent oral and writing skills in English.

Compensation:

• Full-time one year, with possible extension to two years, depending on performance.
• May 2023.
• Competitive salary and benefits.

Application requirements:

• Detailed CV, list of publications, awards and recognitions, and potential start date.
• Short statement of previous work, research interests and his/her future vision on the field.
• Names and contact information of three referees.
• PDF of a recent publication considered by the candidate as being representative of his/her research work.

Ubication: Monterrey, Nuevo León. Mexico.

Contact: Global Recruiter Martha J. Navarro mcayon@tec.mx