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Machine Learning Postdoc positions at The Bioinspired Computing Laboratory at USP

Country/Region : Brazil

Website : http://www.biocom.icmc.usp.br/index.php

Description

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. degrees.
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, data mining and statistics;
? Good knowledgee of languages and tools, such as R, C, C++ or Java
Eduaction: a PhD degree in computer science, electrical engineering, computer engineering, or a similar area with strong 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: US$32.400,00 + US$4.860,00 (research grant) + airplane tickets + US$2.700,00 (installation support)
Starting date: July 15, 2014
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 Prf. André de Carvalho: andre-AT-icmc.usp.br.
Please mention “Application to Post-Doctoral Position” in the title of your e-mail.

Last modified: 2014-05-22 09:16:25