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Formation/mobilité à l'étranger_Faculté des Sciences Exactes

 

Faculté des Sciences Exactes

Programme de mobilité de courte durée et de

perfectionnement à l'étranger (Année 2024)

  

Dépôt des demandes 

Le dépôt des demandes se fera exclusivement en lignesur une plateforme dédiée : 

http://mobilite.univ-bejaia.dz/

Période de dépôt des demandes : 27 mars au 10 avril 2024,

N.B : Toute demande non-enregistrée en ligne ne sera pas prise en compte.


Classement des demandes

Le classement des demandes de mobilité se fera par catégorie et/ou grade, conformément aux grilles d'évaluations jointes à l'arrêté ministériel n°255 du 25/02/2024, fixant les critères de sélection d'admissibilité au programme de perfectionnement à l'étranger.

A cet effet, le candidat à la mobilité (Enseignant-Doctorant-ATS) qui dépose une demande en ligne est invité à:

Télécharger de la même plateforme la grille d'évaluation (version Excel) correspondant à sa demande, la renseigner et la téléverser sur le même espace. Merci de rajouter juste votre NOM au nom du fichier: "NOM_Grille .. .xlsx.

Déposer la version papier de la grille (signée) au Comité Scientifique du Département de rattachement (CSD), avant le lundi 15 avril 2024 à 15h30accompagnée de toutes les pièces permettant de justifier toute activité/production indiquée dans la fiche. 

Pour les justificatifs, il n'est pas nécessaire de charger le dossier. Il suffit de fournir : "la 1ère page pour une publication", "l'attestation de participation pour une communication", "la page de garde avec cachet pour une thèse/mémoire soutenu(e)", "la couverture pour un ouvrage scientifique édité (ISSN/ISBN visibles)" ... etc. Aussi, le justificatif du grade/statut n'est pas nécessaire.

Après vérification des dossiers au niveau des CSD, les demandes enregistrées seront classées par le Conseil Scientifique de la Faculté (Voir le PV CSF-SE n°02 du 27-02-2024).


1. Séjour Scientifique de Haut Niveau de courte durée à l’étranger

Durée de séjour (avec indemnités)* : 07 à 15 jours

Catégories concernées: Prof, MCA et MCB

Grille d'évaluation: "Grille Prof, MCA et MCB.pdf".   

Grille en Excel à renseigner : "Grille_SSHN2024" (Disponible aussi sur la plateforme dédiée à la mobilité). 


2. Stage de Perfectionnement à l’étranger

Durée de séjour (avec indemnités)*15 à 30 jours

Catégories concernées: "Enseignants inscrits en thèse"(MAA,MAB) et "Doctorants non-salariés".

Grille d'évaluation: "Grille Enseignants inscrits en thèse(MAA,MAB)+Doctorants non-salariés.pdf".

Grille en Excel à renseigner :  "Grille_Stage Perf.2024" (Disponible aussi sur la plateforme dédiée à la mobilité).


3. Participation à une manifestation scientifique à l’étranger

Durée de Séjour (avec indemnités)*: Inférieure ou égale à 07 jours

Catégories concernées: Prof, MCA, MCB, Enseignant-chercheurs inscrits en thèse (MAA,MAB) et Doctorants non-salariés

Grille d'évaluation: "Grille Prof, MCA, MCB, MAA et MAB inscrits en thèse, Doctorants non-salariés.pdf". 

Grille en Excel à renseigner : "Grille_Part Manif.Sci.2024" (Disponible aussi sur la plateforme dédiée à la mobilité).


Très important (Dispositions communes à 1., 2. et 3. ci-dessus)

♦ La prise en charge de la billetterie d'avion se fera à hauteur de ..... 000 Da au max. (il sera indiqué utérieurement)

♦ Les Frais d'inscription aux manifestations scientifiques sont limités à ...00 euros au max. (il sera indiqué utérieurement)

♦ Tout départ en formation/mobilité (ou annulation) doit être confirmé le plus tôt possible, auprès du service des stages de la faculté.

♦Toute prolongation de séjour* (jusqu'à 15 jours max pour 1.jusqu'à 30 jours max pour 2. et jusqu'à 7 jours max pour 3.), sans aucune incidence financière supplémentaire, est soumise  à une autorisation au préalable.


 

Doctoral training program in Computer Sciences

This doctoral training is intended for holders of a Master's degree in Computer Science. It aims to train teacher-researchers in Computer Science and researchers capable of taking charge of development projects.  The main areas of research are Artificial Intelligence,  networks and security, distributed systems, and data science. Several projects are underway as part of this program, we can cite:  Artificial intelligence and medicine (diagnosis, prediction, detection); Machine and deep learning; mage processing; Data mining; Cloud computing;  Internet of things and QoS in the context of IoT; Data security; Big data; Problem solving; Satisfiability; Security.

Doctoral training program in Applied Mathematics

Objectives assigned to doctoral training     

  1. Description of the training (Research axes):     

Doctoral training is sponsored by the research teams of the LaMOS research unit, whose axes are described below by key words:           

  1. a) Team N°1: MCO (Cybernetic Methods and Optimization)

Decision-making process in a competitive or cooperative environment, Mathematical programming, multi-criteria decision-making methods, game theory, financial mathematics, futures market, negotiation problems, clustering, bin-packing, industrial organization, transport networks, Adhoc networks, network security.         

  1. b) Team N°2: SR2 (Systems with Reminders and Networks)

Queues with callbacks, Priority, Vacations, negative arrivals, Petri nets, Approximation methods, Strong stability, Performance evaluation, Stochastic comparison, stochastic decomposition     

  1. c) Team N°3: CSQ (Statistical Quality Control)

        Statistical Methods, Non-Parametric Estimation.     

  1. d) Team N°4: PA2 (Random Processes and Applications)

Markov chains; Disturbance terminals; Strong stability; Entropy approach; Development in Taylor series, risk models, inventory management, QDB models,…           

  1. e) Team N°5: FSE2 (Reliability of Electro-Energetic Systems)

Electrical reliability, Mechanical reliability, Graph Theory, Performance evaluation, industrial systems (mechanical, computer, electrical engineering, electronics, telecommunications)     

  1. f) Team N°6: OCO (Optimization and Optimal Control)

Mathematical programming, Optimization, Optimal control.     

  1. Objectives related to the training of trainers:

The evolution of the number of students in the IT and operational research fields requires a strengthening (in terms of staff) of the teaching teams for quality training. Moreover, on the qualitative side, the evolution of computer science and information and decision support systems require continuous updating of knowledge in these areas. The seminars for doctoral students will be used primarily for doctoral students, but also for teaching teams to learn about the latest developments in science in fields related to the themes of doctoral training: Decision-making methods and their applications (transport, computer and communication networks, inventory management, reliability systems, etc.)     

 

  1. Research related objectives:

 The objectives are those of the research projects selected within the framework of doctoral training, in addition to the contribution to the training of doctoral students and the promotion of the research work of the research unit through publications and international and national communications. To this list are added the following objectives:     

  • Find new modeling tools that take into account as many parameters as possible describing complex systems in order to assess their current performance and to predict others in the future in the event of a variation in these parameters.
  • Provide theoretical and practical means that allow us to obtain a better quality of service from these different complex systems.
  • The development of new models and methods to improve, evaluate and optimize the performance of wireless channel access techniques and to optimally manage existing resources using well-adapted protocols.
  • The choice of the adequate protocol which can be done according to several criteria. The simultaneous consideration of these criteria brings us back to the resolution of a multi-criteria problem. Moreover, taking into account several users (stations) wishing to transmit data highlights an interaction situation that can be modeled by game theory.
  • Proposal of opportunistic routing protocols for mesh networks / VANETs. These protocols must efficiently explore the network and search for the best available paths in terms of QoS.
  • Machine learning: In the presence of data, artificial intelligence methods in general and machine learning in particular can be very effective in managing bandwidth (wireless channel).
  • Design statistical and valid techniques for data collection,
  • Develop statistical methods for statistical inference from collected data
  • Improve statistical models for future use based on these experiences.
  • Development of new efficient algorithms for learning SVMs and their applications in various sectors, such as: health, economy and industry.
  • Proposal of a new method for determining the efficient frontier in mean-variance portfolio management via parametric programming.
  • Study the problems of bi-matrix Bayesian games and their application in finance and insurance, as well as in the field of computer security.
  • Obtaining theoretical results on estimation, approximation and modeling in insurance, finance and networks allowing to answer real problems.
  • Assist businesses and insurance companies in the decision-making process to avoid major losses and certain ruin.
  • Better network management and security.
  • Development of appropriate computer applications.

Doctoral training program in Mathematics

1) Statistical and stochastic modelling and inverse problems.

2) Generalized almost periodic functions, fixed-point theory and application to ordinary differential equations.

3) Research methodology (for writing a scientific paper and the thesis).

4) Introduction to pedagogy and didactics.

5) Information and communication technology

6) English (speaking and writing).

Doctoral training program in Chemistry

The objective of doctoral training is to prepare doctoral students for the job search process by helping them identify the multiple skills required in various professional situations. It also guarantees doctoral students a very high level of training and better recognition of their diploma both academically and in industry or services.

The work carried out by the different research teams of the Department of Chemistry aims to contribute to the reinforcement of national competences in the field of materials elaboration, wastewater treatment processes and the development of analytical tools.

In this context, we have proposed reinforcement courses for the specialties related to doctoral training (materials chemistry and environmental chemistry).

-Ecology and sustainable development

-Electrochemistry

-Sensors and biosensors

-Waste prevention and management

-Corrosion

-Modeling of chemical processes

-Study by atomistic simulation of some problems in materials science (seminar)

 

La faculté en chiffres

3451
Etudiants
185
Doctorants LMD
174
Doctorants Classique

Liens Utiles

Licence,Master, Doctorat

Nos formations

Mémoires de fin d'études

Thèses

Pages web de nos enseignants

Enseignants chercheurs

Doctorat et habilitation

Soutenances