The Center of Mathematical Science Applied to Industry, University of Sao Paulo, has one opening for a postdoctoral researchers in machine learning and computational intelligence.

Applicants are expected to have finished, or are about to finish their Ph.D. degree.

We are recruiting a post-doctoral researcher in the area of machine learning, specifically, to investigate the use of novelty detection for industry-related data. The position is located at the Institute of Mathematics and Computer Science (ICMC), University of São Paulo (USP), São Carlos – SP, in Brazil.


The Center of Mathematical Science Applied to Industry, University of Sao Paulo, has one opening for a postdoctoral researchers in machine learning and computational intelligence.

Applicants are expected to have finished, or are about to finish their Ph.D. degree.

We are recruiting a post-doctoral researcher in the area of machine learning, specifically, to investigate the use of novelty detection for industry-related data. The position is located at the Institute of Mathematics and Computer Science (ICMC), University of São Paulo (USP), São Carlos – SP, in Brazil.

More information of our research activities can be found at:

http://www.biocom.icmc.usp.br/index.php
REQUIRED SKILLS AND EXPERTISE:

  • Very good knowledge of written and spoken English (Portuguese is not required);
  • Strong background knowledge in machine learning or data mining;
  • Good knowledgee of languages and tools, such as R, C, C++ or Java

EDUCATION: a PhD degree in computer science, electrical engineering, computer engineering, or a similar area with good publication record.

MISSION: Traditional data mining techniques are designed to deal with static databases, where the underlying probability distribution that generates these data are assumed to be stationary. However, in recent years, a growing amount of streaming data has become available. A data stream can be a massive unbounded sequence of examples continuously
generated at a high-rate, such as networks, sensor data, mobile data, and web click streams that may change for some time scale. In these scenarios, it is not possible to store all the examples that arrive and learning algorithms have to be able to update their decision models always that new examples become available. This project intends to investigate different methods to cope with novelty detection in data streams. An important requirement when dealing with data streams is the capability to learn a model that represents the data evolution over the time, aggregating concept drifts and novelties. This project aims to investigate different algorithms and strategies of dealing with novelty detection in data stream problems. In this study we consider that a novelty is composed by a set of cohesive examples and can be represented by one or more clusters.

ANNUAL SALARY: R$ 73.716,00 + Research grant + airplane tickets + installation support

Possibility of spend part of the posdoc abroad

Starting date: immediate

If you are interested in this position and believe that you qualify, please send a cover letter, a résumé with a list of publications, and the names, e-mail addresses and phone numbers of at least three references to:

Prof. André de Carvalho: andre@icmc.usp.br.
Please mention “Application to Post-Doctoral Position” in the title of your e-mail.