Return to the list
post-doc: Postdoctoral position available in Mexico
Where: Monterrey, Nuevo León,
Mexico
What: 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 research 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.
- Starting date is April 2023. Applications should be submitted by Monday 27 of
February, 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.
Interested applicants should send documentation to:
- Dr. Hugo Terashima-Marin (terashima@tec.mx) and Dr. Carlos A. Coello-Coello
(ccoello@cs.cinvestav.mx)
- Please use as subject for your email: PostDoc Application – MOHH
Who: Hugo Terashima-Marín <terashima@tec.mx>
When: Until 2023-09-30 01:00
Presented at next GECCO?: yes
Return to the list
post-doc: Postdoctoral position available in Mexico
Where: Monterrey, Nuevo León,
MexicoWhat: 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 research 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.
- Starting date is April 2023. Applications should be submitted by Monday 27 of
February, 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.
Interested applicants should send documentation to:
- Dr. Hugo Terashima-Marin (terashima@tec.mx) and Dr. Carlos A. Coello-Coello
(ccoello@cs.cinvestav.mx)
- Please use as subject for your email: PostDoc Application – MOHH
Who: Hugo Terashima-Marín <terashima@tec.mx>
When: Until 2023-09-30 01:00
Presented at next GECCO?: yes
Return to the list