M2 Stochastic tools and Computational Methods for Decision (MSID)

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M2 Stochastic tools and Computational Methods for Decision (MSID)

Presentation

Presentation

Applications are now open here https://aap-e2s.univ-pau.fr/siaap/pub/appel/view/5

Applications will be closed on April 24th, 2020

This program offers advanced level courses in statistical analysis, decision computer science, computer modeling and associated computer tools.

 

Objectives

This programme aims to provide strong skills in stochastic modeling and statistical methods for data analysis, combined with the associated computer tools.

  • Courses focus on applications in the industry, especially in the areas of quality control and safety analysis, but also on applications in data mining and machine learning.

  • Courses are taught by academics but also by engineers

Depending on the  excellency of students and their desire to pursue doctoral studies, courses about « advanced statistics » and « advanced applied probability » can be offered.

Knowledge and skills

At the end of this program, the students in "Stochastic tools and Computational Methods for Decision" will be able to:

  • Conduct an appropriate statistical analysis

  • Apply any classical statistical methods

  • Construct and analyse an experimental design

  • Suggest and analyse a stochastic model

  • Implement stochastic simulation methods

  • Manage databases

Additional information

Scholarships
  • Region Aquitaine Scholarships for non-EU students
  • E2S Talent's Academy Scholarships for all students
International Welcome Desk

Admission

Access condition

LANGUAGE REQUIREMENTS

CECRL B2 level in English,

All teaching materials will be provided both in English and French. Students are allowed to use English or French during exams.

ADMISSION REQUIREMENTS

All students who have completed four years in a higher education institution can apply.

Limited number of students: 30 per year

 

And after

Further studies

Doctoral studies, either in an academic context or in an industrial context 

Job opportunities

Sectors:
  • Industry, services, academic
 Fields
  • Dependability and reliabilty analysis (RAMS), data processing, biomedecine
 Positions:
  • RAMS engineer, statistical analysist, datascientist, data processing engineer, biostatistician, PhD students

Contact(s)

Organizational unit

Administrative contact(s)

Secrétariat de Mathématiques

Email : secretariat-mathematiques @ univ-pau.fr

Places

  • Pau

More info

ECTS credits 60

Type of education

  • Foreign students
  • Ongoing training

Number of students 30

Internship Mandatory (5-6 months)

Registration
From October 18, 2019 to April 24, 2020

Teaching start
September 1, 2020