Context: All the job offers will be done in the context of SEPIA team specialised in large scale distributed systems (HPC and Clouds), particularly in autonomic computing, scheduling and multi-objective optimization. SEPIA team is part of IRIT lab (750 staff members) in Toulouse.
Master Internship offer in the context of the Datazero project
This subject is in the context of the DATAZERO project funded by ANR (French National Funding Agency). This project is a collaboration with FEMTO (Belfort), LAPLACE (Toulouse) laboratories and with EATON company (Grenoble) and focuses on optimization of datacenters using renewable energy sources. In this subject we are interested in optimizing the energy sources commitment (i.e. the scheduling at different timescales of the power output of each component in the power system) to deal with servers load. The different energy sources considered are: wind turbines, solar panels, storage elements (like battery and fuel cell). A connection to the traditional grid will be possible for selling purpose in case of over-production. Different time windows will be considered to address mid / long term scheduling. Different profile demands will be dealt with: predicted energy requested demands and probabilistics demands. In this master thesis we aim to study the dynamic adaptation of the energy units commitment in order to improve energy efficiency.
PhD thesis offers in the context of the i-nondations project
These PhD thesis will be done in the context of the i-Nondations (e-flooding) project funded by ANR (French National Funding Agency). This project is a collaboration with Cerema, IRSTEA, Enedis and SDIS31. Every year floods happen. Solutions exist for slow floods but fast ones are difficult to predict and to handle. This project aims to model fast floods in term of risk management and impact on the infrastructures using data collected by technological or human sensors. The project will integrate different technical expertise to handle fast floods in crisis management and resilience. The project aims to integrate different expertises in an autonomic approach for a fluid adaptation to the evolutions and to the events. The project suggests managing three phases: before, during, and after a crisis in a feedback loop coming from the autonomic field called MAPE-K loop . It is based on four steps : Monitoring, Analysis, Planning and Execution with a Knowledge database. The Knowledge database will be filled continuously in order to identify similarity between events, study answers (and optimize answers) and construct different solutions to handle crisis. Two loops will be used : one for short term timescale and one for long term. The short term one will aim to handle the crisis while the long term one will aim to prevent other crisis. Both loops will interact through a learning process.
In this context, two PhD subjects are proposed: