Requisitos para ser socio

ARTÍCULO 2.2. Para ingresar a la SMF, la persona que desee ser socio presentará una solicitud de ingreso apoyada por dos socios activos que será analizada y en su caso aceptada por la Mesa Directiva. Si fuese aceptado, el solicitante será miembro cuando haya pagado la cuota correspondiente del año en curso.

Recibo de*: Donativo Cuota (IVA 16%)
Socio titular $1,300.00 MXN $1,508.00 MXN
Socio estudiante $650.00 MXN $754.00 MXN

*La SMF expide dos tipos de recibos: “Donativo” y “Cuota de Inscripción”. La diferencia principal es que el segundo incluye 16% de IVA y generalmente es el tipo de comprobante que aceptan las instituciones.

ICTP South American Institute for Fundamental Research

ICTP-SAIFR

ICTP South American Institute for Fundamental Research

2nd Latin American  School on Parallel Programing for High Performance Computing

Start time: December 2, 2019

Ends on: December 13, 2019

Location: São Paulo, Brazil

Venue: NCC-UNESP

Description: 

The goal of the school is to teach scientists modern computer hardware and programming to provide a foundation for future computational research using High Performance Computing (HPC). Participants will go through an intensive programme with focus on practical skills.

Participants will learn how to improve the efficiency of their research codes, and to parallelize them. Lectures on a selection of technical aspects of modern HPC hardware will be mixed with introductions to widely used parallel programming tools and libraries. The hands-on sessions will allow participants to learn from examples of problems of general scientific interest. Topics will cover numerical methods and parallel strategies, as well as data management.

The programme specifically addresses the needs of scientists using, writing, or modifying HPC applications, and will not assume, require, or provide significant IT and HPC resource management skills. It will be mainly based on fundamental HPC-relevant features in widely used scientific software for high-performance computing.

There is no registration fee and limited funds are available for travel and local expenses.

Topics:

  • Computer architectures for HPC and optimization
  • Parallel programming tools (MPI & OpenMP)
  • Parallel programming best practices
  • Floating-point math
  • Profiling and Debugging
  • Principles and Practices of Parallel SW Development

Lecturers:

  • Ivan Girotto (ICTP-Trieste, Italy)
  • Axel Kohlmeyer (Temple University, Philadelphia, US)
  • Gavin Pringle (EPCC, Edinburgh, UK)
  • Silvio Luiz Stanzani (NCC-UNESP/AI2, Brazil)

Organizers:

  • Raphael Cobe (NCC-UNESP/AI2, Brazil)
  • Ivan Girotto (ICTP-Trieste, Italy)
  • Sergio F. Novaes (UNESP/AI2, Brazil)
  • Silvio Luiz Stanzani (NCC-UNESP/AI2, Brazil)

Registration deadline: September 29, 2019

 

Informationhttps://www.ictp-saifr.org/school-on-parallel-programing-for-high-performance-computing/

 

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First ICTP-SAIFR/AI2 School on Data Science and Machine Learning

 

Start time: December 16, 2019

Ends on: December 20, 2019

Location: São Paulo, Brazil

Venue: NCC-UNESP

Description: 

Machine Learning (ML) concepts will drive some critical changes in our society during the next decades. The cross-cutting character of the ML tools can be used to attack a wide variety of problems that could improve our lives, for instance, designing solutions for medical diagnosis, providing smart assistance to the disabled and the elderly and building solutions for public safety. The positive impact of these applications is expected to raise awareness on the subject and it will guide the creation of new public policies. In that, sense, the training of people on the most advanced topics in ML is very important for the success and development of the area.

The School on Data Science and Machine Learning has the goal of teaching participants about modern machine learning techniques, their strengths and shortcomings, and how to apply them in different contexts. The school is targeted particularly at senior PhD students, working towards the completion of their thesis projects, as well as young postdocs.

The school participants will learn the formalism of machine learning, starting from an introductory level and going through more advanced topics like computer vision, sequential and recursive learning, anomaly and outlier detectors, and generative models. The theoretical lectures will be mixed with a set of hands-on sessions where participants will be able to apply the concepts to solving real-world problems.

There is no registration fee and limited funds are available for travel and local expenses.

Lecturers:

  • Reinaldo A. C. Bianchi (FEI, Brazil)
  • André Carlos Ponce de Leon Ferreira de Carvalho (ICMC – USP, Brazil)
  • Anna Helena Reali Costa (EP-USP, Brazil)
  • Alexandre Xavier Falcão (IC-UNICAMP, Brazil)
  • Marcelo Finger (IME-USP, Brazil)
  • João Paulo Papa (FC-Unesp, Brazil)
  • Felipe Leno da Silva (EP-USP, Brazil)

Organizers:

  • Nathan Berkovits (ICTP-SAIFR/IFT-UNESP, Brazil)
  • Raphael Cobe (NCC-UNESP/AI2, Brazil)
  • Sergio F. Novaes (UNESP/AI2, Brazil)
  • Maria Spiropulu (Californa Institute of Technology, USA)
  • Thiago Tomei (NCC-UNESP/AI2, Brazil)

Application deadline: October 13, 2019

Informationhttps://www.ictp-saifr.org/school-on-data-science-and-machine-learning/

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Victor Maya Higuera
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