2 postdoc positions and 1 technical training position in Geoinformatics and Remote Sensing

European Geosciences Union e.V.; Piracicaba; Teletrabalho; BRL 20.000 - 80.000; Tempo integral

Resumo da oferta

An innovative program seeks two postdoctoral researchers and a technical training professional in Geoinformatics and Remote Sensing. This exciting opportunity involves developing a decision-making platform to enhance vegetation coverage in São Paulo. Candidates will work with interdisciplinary teams, utilizing advanced geospatial modeling and remote sensing techniques. The positions offer a chance to contribute to significant environmental restoration efforts while collaborating with public managers and NGOs. If you have a strong background in geospatial analysis and a passion for sustainability, this role is perfect for you.

Qualificações

• Strong publication records and expertise in geospatial modeling or remote sensing.
• Experience with drone and satellite data, applying machine learning techniques.

Responsabilidades

• Develop geospatial models for restoration prioritization.
• Create and organize databases, collect field data with drones.

Conhecimentos

Python

SQL

Geospatial databases

Remote sensing

Machine learning

Deep learning

WebGIS

Formação académica

PhD

Bachelor's degree

Master's degree

Ferramentas

GNSS

Drones

Descrição da oferta de emprego

2 postdoc positions and 1 technical training position in Geoinformatics and Remote Sensing

Employer

Energy, Resources and the Environment (ERE)

Type

Contract

Level

Experienced

R$ 12,000/month, 36 months

Required education

PhD

25 May 2025

Posted

6 May 2025

FAPESP Project: RedeFloresta: Geospatial decision support platform for the restoration of landscapes and ecosystems in the state of São Paulo (Public Policy Research Program – PPPP)

FAPESP process number: 2023/09862-7

Supervisor: Prof. Pedro Henrique Santin Brancalion

Co-Supervisors: Profª. Catherine Torres de Almeida (UFPR), Prof. Paulo Guilherme Molin (UFSC)

The ReflorestaSP program, from the Secretariat of Environment, Infrastructure and Logistics of São Paulo, aims to increase vegetation coverage by 700 thousand hectares by 2050. To achieve this, a strategic plan to prioritize areas for restoration and monitor interventions is needed.

The RedeFloresta project aims to develop an online decision-making platform to generate maps identifying priority areas for restoration and monitor them using remote sensing data.

We seek 2 postdoctoral candidates with strong publication records and expertise in geospatial modeling (PD#1) and remote sensing (PD#2), to create and analyze scenarios supporting decision-making. Additionally, a TT4 technical training position is available for professionals to contribute to the platform's development, including database creation and field data collection with drones and GNSS.

The selected candidates will collaborate with interdisciplinary teams from ESALQ/USP, UFPR, UFSC, UNESP, and other institutions, working with public managers and NGOs like PACTO, SOS Mata Atlântica, WWF, IPE, and TNC. The workplace is in Piracicaba/SP, with occasional travel to São Paulo/SP and Curitiba/PR.

The postdoctoral fellowship (R$12,000/month) lasts 36 months, with a 10% annual reserve, requiring a PhD. The TT4 fellowship (R$4,320/month) lasts 24 months, requiring a bachelor’s degree with 2+ years of experience or a master’s degree, with 40 hours/week commitment. Positions are open to Brazilian and foreign researchers. Proficiency in Portuguese is required.

The selection process includes analysis of a letter of interest, curriculum, online interview, and proof of degree. Interested candidates should complete the respective application forms or contact via email at [e-mail].

Positions:

1. PD#1 – Multicriteria modeling for restoration prioritization: develop a geospatial model combining ecological and socioeconomic indicators, requiring knowledge of Python, SQL, and geospatial databases; experience with WebGIS is a plus.
2. PD#2 – Remote sensing for multiscale monitoring: work with drone and satellite data, applying machine learning/deep learning techniques, requiring knowledge of remote sensing and programming; experience in forest inventory and WebGIS is desirable.
3. TT4 – WebGIS and geospatial databases: create and organize databases, collect field data with drones and GNSS, with knowledge of WebGIS development.