Postdoctoral position in machine learning applied to radar imagery

Updated: 2 months ago
Job Type: FullTime
Deadline: 12 Feb 2026

22 Jan 2026
Job Information
Organisation/Company

Universidade Estadual Paulista (UNESP)
Department

Computer Science
Research Field

Computer science
Researcher Profile

Recognised Researcher (R2)
Positions

Postdoc Positions
Application Deadline

12 Feb 2026 - 23:59 (America/Argentina/Buenos_Aires)
Country

Brazil
Type of Contract

Temporary
Job Status

Full-time
Hours Per Week

40
Offer Starting Date

1 Mar 2026
Is the job funded through the EU Research Framework Programme?

Not funded by a EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Accurate analysis and interpretation of meteorological data obtained through radar are fundamental for weather forecasting and monitoring severe weather events. Radar images, especially those of the PPI (Plan Position Indicator) and SAR (Synthetic Aperture Radar) types, often present significant challenges that compromise their interpretation, including speckle noise, attenuation effects, altitude variations, and artifacts caused by atmospheric interference. Furthermore, the inherent complexity of different radar types and their specific configurations hinders the creation of generalizable solutions for processing these images. This project proposes an innovative approach that combines state-of-the-art diffusion models with physical radar knowledge and advanced transfer learning techniques. The methodology incorporates fundamental radar wave propagation equations into the diffusion process, allowing for more accurate and physically consistent image restoration. The developed framework will be able to transfer knowledge between different radar types (PPI, SAR, Doppler) and adapt to different meteorological conditions through a continuous feedback system based on radar-specific metrics. Please, send your CV (Lattes if you are Brazilian) to the email joao.papa@unesp.br


Where to apply
E-mail

joao.papa@unesp.br

Requirements
Research Field
Computer science » Other
Education Level
PhD or equivalent

Skills/Qualifications

Experience in machine learning, math, and programming.


Languages
ENGLISH
Level
Good

Additional Information
Work Location(s)
Number of offers available
1
Company/Institute
Univer
Country
Brazil
State/Province
Universidade Estadual Paulista (UNESP)
City
Bauru
Postal Code
17033-360
Street
Av. Eng. Luiz Edmundo Carrijo Coube, 14-01
Geofield


Contact
State/Province

São Paulo
City

Bauru
Website

https://www2.unesp.br/
Street

Av. Eng. Luiz Edmundo Carrijo Coube, 14-01
Postal Code

17033-36014884-900
Fax

+551431036079

STATUS: EXPIRED

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