Post-doctoral position in Multi-constraint Allocation and Placement

Job description

ABOUT TELECOM SUDPARIS

Telecom SudParis is a public graduate school for engineering, which has been recognized on the highest level in the domain of digital technology. The quality of its courses is founded on the scientific excellence of its faculty and on teaching techniques that emphasize project management, innovation and intercultural understanding. Telecom SudParis is part of the Institut Mines-Telecom, the number one group of engineering schools in France, under the supervision of the Minister for Industry. Telecom SudParis with Ecole Polytechnique, ENSTA Paris, ENSAE Paris and Telecom Paris are co-founders of the Institut Polytechnique de Paris, an institute of Science and Technology with an international vocation.

Its assets include: a personalized course, varied opportunities, the no.3 incubator in France, an ICT research center, an international campus shared with Institut Mines-Telecom Business School and over 60 student societies and clubs.


MISSIONS :

The research and development work planned in this post-doctoral position consists of designing optimization algorithms for cloud service requests that are heterogeneous in demands and that characterized by very different and multiple constraints. Traditional algorithms seldom address the plethora of constraints that end users express in their cloud services demands. Treating jointly and not sequentially the requests, with long-term rewards for all the stakeholders has been less addressed by the scientific community and deserves more attention. The goal of the Post-Doc is to propose multi-constraints and multi-objective algorithms using graph theory, game theory but also stochastic optimization methods leading to solutions that are more robust. Evolutionary approaches to the problem should be considered and explored as well.


ACTIVITIES :

The research and development work consists in modeling the problem, investigating several algorithms and approaches to solve this unexplored subject of fulfilling simultaneously very different and heterogeneous constraints expressed by end users. Each imposing constraints and obligation quite distinct and contrasting requirements and preferences actors.

The developed algorithms will be evaluated in terms of achievable performance, complexity, scalability and compared with against the state of the art.

Job requirements

LEVEL OF TRAINING AND/OR EXPERIENCE REQUIRED:

- PhD or Doctorat for less than 3 years in combinatorial and convex optimization, stochastic optimization, computer science and networks

ESSENTIAL SKILLS, KNOWLEDGE AND EXPERIENCE:

- In depth knowledge of combinatorial and convex optimization, in evolutionary optimization techniques, metaheuristics and modeling of various systems and networks

ADVANTAGEOUS SKILLS, KNOWLEDGE AND EXPERIENCE:

- Stochastic optimization methods, game theory, graph theory knowledge are key skills for this position. Software development and coding capabilities highly desirable for increased accomplishment and success

ABILITIES AND SKILLS:

- Capable of team work

- Autonomous

- Scientific rigor

- Software development skills

- Real abilities to contribute to editing of deliverables in collaborative and advanced skills in publishing results and accomplishments both in French and English in highly ranked journals and conferences


ADDITIONAL INFORMATION AND APPLICATION:
- Application deadline: July 31, 2022
- Nature of the contract: CDD / limited contract 15 months
- Job category and profession: II - P, Post-doctoral fellow
- The positions offered for recruitment are open to all with, on request, accommodations for candidates with disabilities
- Job open to public service contractors

- Localisation: Palaiseau (91)