Call for applications

Postdoc position

* Machine Learning / Computer Vision *

University of São Paulo (USP), Brazil

Application period: October/November, 2019

We have a postdoc position for plankton image processing and analysis, with focus on semi-supervised and user-interactive methods.

This opportunity is open to applicants of any nationality. The host project, World Wide Web of Plankton Image Curation (WWW.PIC), is an international project promoted by Belmont Forum, with participation of teams from France, United States, Brazil and Japan. The postdoc fellow will be part of the Brazilian team, will be primarily working at Institute of Mathematics and Statistics, and occasionally at the Oceanographic Institute, both at University of São Paulo, São Paulo, Brazil, and will have opportunities to interact with researchers from these countries. There is a fellowship from FAPESP for this position (see details below).

Research topic description

    Modern imaging technologies allow acquisition of in situ plankton images in large scale. Recognizing and estimating their distribution on distinct taxonomic classes is of great importance for better understanding the marine ecosystem. Machine assisted methods for the recognition of these organisms are fundamental for timely processing and analysis of these data.

    In this scenario, deep learning techniques emerge as a promising tool. However, the data-hungry nature of deep learning models is a challenge for their effective use, specially considering data that may have distinct characteristics depending on many factors such as season of the year, imaging technology, resolution, location where images are acquired, weather conditions, unknown species, and so on.

    The main goal of the postdoc project is to develop machine learning based computational methods to speed up both annotation and classification of plankton images and at the same time minimize the required effort from the expert. That is, we do not wish to simply restart training for each new batch of data nor we would like to rely on experts manually labeling thousands of images for each situation. We would like to be able to effectively reuse previously generated knowledge to quickly produce a classifier adapted to the new imaging or use conditions.

    The focus of the research should be on semi-supervised and user-interaction based methods. Clever user interaction to guide the data labeling and machine training processes and also for validating the results are desirable features for the solution. There is no strong constraint of approaches to be investigated as long as an effective solution is targeted. Developed methods will be integrated into EcoTaxa. As this project will be within an international collaboration, we expect to have access to distinct batch of images, coming from different equipment and imaging conditions.


  • Ph.D. in Computer Science or related fields
  • Ability to work independently as well as with an interdisciplinary team
  • Strong background in machine learning, experience with deep learning, solid programming skills
  • Previous experience with image processing, data analysis and visualization, or user-interaction related projects will be a plus
  • Any interest in optics and/or biology is also welcome


  • The selected candidate will be awarded with a FAPESP Post-Doctoral fellowship. It includes a monthly stipend of R$ 7,373.10 [1] plus a research contingency fund of 15% of the annual value of the fellowship, each year. For more details, please see, modality (a) -- the process to which the fellowship is linked is 2018/24167-5.
  • doctorate degree must have been earned no longer than seven years before the beginning of the postdoc fellowship
  • The fellowship is yearly renewable, for up to three years

Application instructions

  • The position is available immediately, with application subject to approval by FAPESP
  • Applications will be accepted until the position is filled
  • Interested candidates should submit an email to, with subject [WWW.PIC] Postdoc application, containing the following information:
    • a CV
    • a brief cover letter explaining research experiences, how research interests fit the goals of the project, career plans, and convenient starting date
    • the names and contact information of three references familiar with the applicant's research and academic work

Further information

    For additional information, please contact

[1] the following link gives an estimative of the cost of living in São Paulo city: